MongoDB vs MySQL vs PostgreSQL

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MongoDB vs MySQL vs PostgreSQL: What are the differences?

Introduction

MongoDB, MySQL, and PostgreSQL are all popular database management systems (DBMS) used in web development. While they share similarities in terms of being relational and supporting SQL, they also have key differences that make them suitable for specific use cases. In this markdown, we will discuss the key differences between MongoDB, MySQL, and PostgreSQL.

  1. Data Model: MongoDB and MySQL are both non-relational databases, whereas PostgreSQL is a relational database. MongoDB uses a flexible document model, storing data in the form of JSON-like documents. MySQL uses a table-based data model, where data is organized into tables with predefined columns and rows. PostgreSQL follows the relational data model, storing data in tables that are related through primary and foreign keys.

  2. Scalability: MongoDB is designed to scale horizontally, allowing for the distribution of data across multiple servers. It excels in handling large amounts of unstructured data and can easily accommodate high-traffic websites. MySQL and PostgreSQL are more suited for vertical scalability, scaling up with more powerful hardware. They are suitable for applications with complex relationships and strict data integrity requirements.

  3. Query Language: MongoDB has its own query language called the MongoDB Query Language (MQL). MQL is based on JavaScript and provides powerful querying capabilities, including support for complex aggregations and real-time data processing. MySQL and PostgreSQL both use SQL as their query language, which is standardized and widely supported. SQL provides a structured and well-defined approach to querying and manipulating data.

  4. ACID Compliance: ACID (Atomicity, Consistency, Isolation, Durability) is a set of properties that guarantee reliability and consistency in database transactions. MySQL and PostgreSQL are fully ACID-compliant, ensuring data consistency and reliability. MongoDB, on the other hand, sacrifices some ACID properties for the sake of scalability and performance. It supports atomic operations on a single document but does not guarantee consistency across multiple documents in a transaction.

  5. Replication and High Availability: MongoDB provides built-in support for automatic replication and high availability through its replica sets. Replica sets allow for the automatic synchronization of data across multiple servers, ensuring data redundancy and failover capabilities. MySQL and PostgreSQL also support replication and high availability but require additional configuration and setup.

  6. Schema Flexibility: MongoDB offers schema flexibility, allowing for dynamic and flexible data models. It does not enforce a predefined schema, making it easy to adapt and evolve the data structure as requirements change. MySQL and PostgreSQL, being relational databases, have a rigid schema that defines the structure of the data. Any changes to the schema require altering the tables and can be more time-consuming.

In summary, MongoDB stands out with its flexibility, horizontal scalability, and powerful querying capabilities, making it suitable for handling large amounts of unstructured data. MySQL and PostgreSQL are better suited for applications with complex relationships, strict data integrity requirements, and the need for full ACID compliance.

Advice on MongoDB, MySQL, and PostgreSQL
Ilias Mentzelos
Software Engineer at Plum Fintech · | 9 upvotes · 239.9K views
Needs advice
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CouchbaseCouchbase
and
MongoDBMongoDB

Hey, we want to build a referral campaign mechanism that will probably contain millions of records within the next few years. We want fast read access based on IDs or some indexes, and isolation is crucial as some listeners will try to update the same document at the same time. What's your suggestion between Couchbase and MongoDB? Thanks!

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Replies (2)
Jon Clarke
Enterprise Account Exec at ScyllaDB · | 4 upvotes · 87.1K views
Recommends
on
CouchbaseCouchbaseScyllaDBScyllaDB

I am biased (work for Scylla) but it sounds like a KV/wide column would be better in this use case. Document/schema free/lite DBs data stores are easier to get up and running on but are not as scalable (generally) as NoSQL flavors that require a more rigid data model like ScyllaDB. If your data volumes are going to be 10s of TB and transactions per sec 10s of 1000s (or more), look at Scylla. We have something called lightweight transactions (LWT) that can get you consistency.

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Recommends
on
MongoDBMongoDB

I have found MongoDB highly consistent and highly available. It suits your needs. We usually trade off partion tolerance fot this. Having said that, I am little biased in recommendation as I haven't had much experience with couchbase on production.

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Needs advice
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MongoDBMongoDBMySQLMySQL
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PostgreSQLPostgreSQL

I'm planning to build a freelance marketplace website, using tools like Next.js, Firebase Authentication, Node.js, but I need to know which type of database is suitable with performance and powerful features. I'm trying to figure out what the best stack is for this project. If anyone has advice please, I’d love to hear more details. Thanks.

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Replies (3)
Reza Malek
at Meam Software Engineering Group · | 9 upvotes · 185K views
Recommends
on
PostgreSQLPostgreSQL

Postgres and MySQL are very similar, but Mongo has differences in terms of storage type and the CAP theorem. For your requirement, I prefer Postgres (or MySQL) over MongoDB. Mongo gives you no schema which is not always good. on the other hand, it is more common in NodeJS community, so you may find more articles about Node-Mongo stuff. I suggest to stay with RDBMS if possible.

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Recommends
on
MySQLMySQLPostgreSQLPostgreSQL

This is a little about experience. Postgresql is fine. You can use either the related table structure or the json table structure.

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Ruslan Rayanov
Recommends
on
MySQLMySQL

We have a ready-made engine for the online exchange and marketplace. To customize it, you only need to know sql. Connecting any database is not a problem. https://falconspace.site/list/solutions

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Dennis Kraaijeveld
Needs advice
on
ExpressJSExpressJSMongoDBMongoDB
and
PostgreSQLPostgreSQL

For learning purposes, I am trying to design a dashboard that displays the total revenue from all connected webshops/marketplaces, displaying incoming orders, total orders, etc.

So I will need to get the data (using Node backend) from the Shopify and marketplace APIs, storing this in the database, and get the data from the back end.

My question is:

What kind of database should I use? Is MongoDB fine for storing this kind of data? Or should I go with a SQL database?

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Replies (3)
Arash JalaliGhalibaf
Software Engineer at Cafe Bazaar · | 10 upvotes · 248.7K views
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PostgreSQLPostgreSQL

Postgres is a solid database with a promising background. In the relational side of database design, I see Postgres as an absolute; Now the arguments and conflicts come in when talking about NoSQL data types. The truth is jsonb in Postgres is efficient and gives a good performance and storage. In a comparison with MongoDB with the same resources (such as RAM and CPU) with better tools and community, I think you should go for Postgres and use jsonb for some of the data. All in all, don't use a NoSQL database just cause you have the data type matching this tech, have both SQL and NoSQL at the same time.

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Recommends
on
MongoDBMongoDB

I have found MongoDB easier to work with. Postgres and SQL in general, in my experience, is harder to work with. While Postgres does provide data consistency, MongoDB provides flexibility. I've found the MongoDB ecosystem to be really great with a good community. I've worked with MongoDB in production and it's been great. I really like the aggregation system and using query operators such as $in, $pull, $push.

While my opinion may be unpopular, I have found MongoDB really great for relational data, using aggregations from a code perspective. In general, data types are also more flexible with MongoDB.

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Luciano Bustos
Senior Software Developer · | 1 upvotes · 238.6K views
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PostgreSQLPostgreSQL

I will use PostgreSQL because you have more powerfull feature for data agregation and views (the raw data from shopify and others could be stored as is) and then use views to produce diff. kind of reports unless you wanna create those aggregations/views in nodejs code. HTH

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Krunal Shah
Technical Lead at Infynno Solutions · | 7 upvotes · 261.1K views
Needs advice
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MongoDBMongoDB
and
PostgreSQLPostgreSQL

I want to store the data retrieved from multiple APIs and perform some analytics on it. The data stored in DB will never/hardly change. First, I thought it would be better to retrieve the data and create table columns for them, but some data might have different columns than others. So I thought about storing the JSON response from API directly to the table and use it. So which database will be the better choice, PostgreSQL or MongoDB.

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Replies (6)
Nikhil Gurnani
Sr. Backend Engineer at Grappus · | 8 upvotes · 253.4K views
Recommends
on
MongoDBMongoDB

Hey Krunal, your requirement sounds pretty clear and specific to what you want to do with that data. My recommendation to you, would be to use MongoDB. Since schema-less IO is faster in MongoDB, your general speed of reading / writing from and to the database would be quick. Additionally, the aggregate framework is very powerful with large data so that is also something that you can use in computing your analytics.

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Maxim Ryakhovskiy
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on
MongoDBMongoDBMongooseMongoose

I suggest you to go with MongoDB, because it is schema-less, i.e., it permits you to easily manipulate the schema of a table. If you want to add a column, it can be done without much effort. Moreover, MongoDB can deal with more types of data, since the latest is stored as key-value pair. I do not what kind of analysis you are going to do, but NoSQL is not the best choice if you are going to use complex queries. In addition, if you are working with huge amount of data and you are interested in optimising the performance, I suggest you PostgreSQL. Since you are speaking about API and JSON, I guess that you may using Node JS for fetching API. I suggest you to try Mongoose, which facilitate the use of MongoDB with Node JS.

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Tarun Batra
Senior Software Developer at Okta · | 3 upvotes · 249.4K views
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MongoDBMongoDBPostgreSQLPostgreSQL

Looks like the use case is to store JSON data. mongoDB and Postgres differ in so many aspects like scaling and consistency. Postgres has excellent JSON support now with the power of SQL. MongoDB is good in handling schema less data. However in this case it seems these differences don’t matter that much. I’d recommend you go with what you are most comfortable with.

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Luiz H. Rapatão
Staff Software Engineer at rapatao.com · | 3 upvotes · 249.4K views
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on
MongoDBMongoDB

I don't have an unquestionable opinion regarding your use case. I only trend to pick the MongoDB since it is schemaless avoiding null columns that you not always know when it is used (it depends on the source of the data). The only drawback that I could consider is the query's complexity in MongoDB, sometimes it is a bit tricky, when compared to the traditional SQL queries.

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Bob Bass
President & Full Stack Enginee at Narro, LLC · | 3 upvotes · 249.3K views
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MySQLMySQLPostgreSQLPostgreSQL

This is largely a matter of opinion. I see that someone else responded and recommended MongoDB but since you are doing data analytics, I highly recommend you go with SQL. You're going to have a really hard time normalizing the data when you can't manipulate relationships and bulk edit with a nice update query.

I'm much more experienced with MySQL than any other database and I am having a hard time getting on board with noSQL entirely because it's really hard to query complex data with relationships using noSQL. I'm using Firestore with one of my apps and MongoDB with another app but they both use MySQL for the heavy lifting and then a document database for things like permissions, caching, etc.

It sounds like the type of problem you need to reverse engineer. I'm sure you can imagine what the data sets would look like if you use MongoDB or Postgres. I suspect that putting in a little bit more work up front will pay high dividends and productivity once the data is normalized.

Again - it's largely a matter of preference but I prefer SQL almost every time.

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Recommends
on
MongoDBMongoDB

MongoDB should be better for unstructured/less structured data.

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Needs advice
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MongoDBMongoDB
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PostgreSQLPostgreSQL

I need urgent advice from you all! I am making a web-based food ordering platform which includes 3 different ordering methods (Dine-in using QR code scanning + Take away + Home Delivery) and a table reservation system. We are using React for the front-end, and I need your advice if I should use NestJS or ExpressJS for the backend. And regarding the database, which database should I use, MongoDB or PostgreSQL? Which combination will be better? PS. We want to follow the microservice architecture as scalability, reliability, and usability are the most important Non Functional requirements. Expert advice is needed, please. A load of thanks in advance. Kind Regards, Miqdad

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Replies (3)
Stephen Badger | Vital Beats
Senior DevOps Engineer at Vital Beats · | 9 upvotes · 268.3K views
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PostgreSQLPostgreSQL
at

I can't speak for the NestJS vs ExpressJS discussion, but I can given a viewpoint on databases.

The main thing to consider around database choice, is what "shape" the data will be in, and the kind of read/write patterns you expect of that data. The blog example shows up so much for DBMS like MongoDB, because it showcases what NoSQL / document storage is very scalable and performant in: mostly isolated documents with a few views / ways to order them and filter them. In your case, I can imagine a number of "relations" already, which suggest a more traditional SQL solution would work well: You have restaurants, they have maybe a few menus (regular, gluten-free etc), with menu items in, which have different prices over time (25% discount on christmas food just after christmas, 50% off pizzas on wednesdays). Then there's a whole different set of "relations" for people ordering, like showing them past orders, which need to refer to the restaurant etc, and credit card transaction information for refunds etc. That to me suggests PostgreSQL, which will scale quite well if you database design is okay.

PostgreSQL also offers you some extensions, which are just amazing for your use-case. https://postgis.net/ for example will let you query for restaurants based on location, without the big cost that comes from constantly using something like Google Maps API to work out which restaurants are near to someone ordering. Partitioning and window functions will be great for your own use internally too, like answering questions of "What types of takeways perform the best for us, Italian, Mexican?" or in combination with PostGIS, answering questions like "What kind of takeways do we need to market to, to improve our selection?".

While these things can all be implemented in MongoDB, you tend to lose some of the convenience of ACID or have to deal with things like eventual consistency, which requires more thinking on the part of your engineers. PostgreSQL offers decent (if more complex) scalablity and redundancy solutions, and is honestly very well proven and plenty of documentation exists on optimising queries.

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Anis Zehani
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on
MongoDBMongoDB

Hello, i build microservice systems using Angular And Spring (Java) so i can't help with with ur back end choice, BUT, i definitely advice you to use a Nosql database, thus MongoDB of course or even Cassandra if your looking for extreme scalability with zero point of failure. Anyway, Nosql if much more faster then Sql (in your case Postresql DB). All you wanna do with sql can also be done by nosql (not the opposite of course).I also advice you to use docker containers + kubernetes to orchestrate them, if you need scalability and replication, that way your app can support auto scalability (in case ur users number goes high). Best of luck

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Carlos Iglesias
Recommends

About PostgreSQL vs MongoDB: short answer. Both are great. Choose what you like the most. Only if you expect millions of users, I‘ll incline with MongoDB.

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Dimelo Waterson
Needs advice
on
MySQLMySQLPostgreSQLPostgreSQL
and
SQLiteSQLite

I need to add a DBMS to my stack, but I don't know which. I'm tempted to learn SQLite since it would be useful to me with its focus on local access without concurrency. However, doing so feels like I would be defeating the purpose of trying to expand my skill set since it seems like most enterprise applications have the opposite requirements.

To be able to apply what I learn to more projects, what should I try to learn? MySQL? PostgreSQL? Something else? Is there a comfortable middle ground between high applicability and ease of use?

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Replies (3)
Recommends
on
SQLiteSQLite

You can easily start with SQlite. Really easy to startup since it doesn't require you to install any additional software since is self-contained. It has interfaces in almost any language and also GUIs. Start learning SQL basics and simpler data models and structures. There are many tutorials, also available in the official website. From there you will easily migrate to another database. MySQL could be next, sonce it's easier to learn at first and has more resources available. PostgreSQL is less widespread, more challenging and has the fewer resorces, but once you have some experience with MySQL is really easy to learn as well. All these technologies are really widespread and used accross the industry so you won't make a wrong decision with any of these.

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Stephen Badger | Vital Beats
Senior DevOps Engineer at Vital Beats · | 6 upvotes · 288.6K views

A question you might want to think about is "What kind of experience do I want to gain, by using a DBMS?". If your aim is to have experience with SQL and any related libraries and frameworks for your language of choice (python, I think?), then it kind of doesn't matter too much which you pick so much. As others have said, SQLite would offer you the ability to very easily get started, and would give you a reasonably standard (if a little basic) SQL dialect to work with.

If your aim is actually to have a bit of "operational" experience, in terms of things like what command line tools might be available as standard for the DBMS, understanding how the DBMS handles multiple databases, when to use multiple schemas vs multiple databases, some basic privilege management etc. Then I would recommend PostgreSQL. SQLite's simplicity actually avoids most of these experiences, which is not helpful to you if that is what you hope to learn. MySQL has a few "quirks" to how it manages things like multiple databases, which may lead you to making less good decisions if you tried to take your experience over to different DBMS, especially in bigger enterprise roles. PostgreSQL is kind of a happy middle ground here, with the ability to start PostgreSQL servers via docker or docker-compose making the actual day-to-day management pretty easy, while still giving you experience of the kinds of considerations I have listed above.

At Vital Beats we make use of PostgreSQL, largely because it offers us a happy balance between good management and backup of data, and good standard command line tools, which is essential for us where we are deploying our solutions within Kubernetes / docker, and so more graphical tools are not always appropriate for us. PostgreSQL is also pretty universally supported in terms of language libraries and frameworks, without having to make compromises on how we want to store and layout our data.

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Julien DeFrance
Principal Software Engineer at Tophatter · | 1 upvotes · 280.1K views
Recommends
on
MySQLMySQL

MySQL's very popular, easy to install, is also available as a managed service across most popular cloud offerings. The support/default tooling (such as MySQL Query Workbench) certainly is a little more baked than what you'll find for Postgres.

https://dev.mysql.com/downloads/workbench/

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Maxim Ryakhovskiy
Needs advice
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MariaDBMariaDBMongooseMongoose
and
PostgreSQLPostgreSQL

Hi all. I am an informatics student, and I need to realise a simple website for my friend. I am planning to realise the website using Node.js and Mongoose, since I have already done a project using these technologies. I also know SQL, and I have used PostgreSQL and MySQL previously.

The website will show a possible travel destination and local transportation. The database is used to store information about traveling, so only admin will manage the content (especially photos). While clients will see the content uploaded by the admin. I am planning to use Mongoose because it is very simple and efficient for this project. Please give me your opinion about this choice.

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Replies (7)

The use case you are describing would benefit from a self-hosted headless CMS like contentful. You can also go for Strapi with a database of your choice but here you would have to host Strapi and the underlying database (if not using SQLite) yourself. If you want to use Strapi, you can ease your work by using something like PlanetSCaleDB as the backing database for Strapi.

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Reza Malek
at Meam Software Engineering Group · | 4 upvotes · 229.3K views
Recommends
on
MongooseMongoosePostgreSQLPostgreSQL

Your requirements seem nothing special. on the other hand, MongoDB is commonly used with Node. you could use Mongo without defining a Schema, does it give you any benefits? Also, note that development speed matters. In most cases RDBMS are the best choice, Learn and use Postgres for life!

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Tarun Batra
Senior Software Developer at Okta · | 2 upvotes · 221.6K views
Recommends
on
MongooseMongoose

MongoDB and Mongoose are commonly used with Node.js and the use case doesn't seem to be requiring any special considerations as of now. However using MongoDB now will allow you to easily expand and modify your use case in future.

If not MongoDB, then my second choice will be PostgreSQL. It's a generic purpose database with jsonb support (if you need it) and lots of resources online. Nobody was fired for choosing PostgreSQL.

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Nutchanon Ninyawee

SQL is not so good at query lat long out of the box. you might need to use additional tools for that like UTM coordinates or Uber's H3.

If you use mongoDB, it support 2d coordinate query out of the box.

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Recommends
on
MongooseMongoose

Any database will be a great choice for your app, which is less of a technical challenge and more about great content. Go for it, the geographical search features maybe be actually handy for you.

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Václav Hodek
CEO, lead developer at Localazy · | 1 upvotes · 221.9K views
Recommends
on
PostgreSQLPostgreSQL

Any database engine should work well but I vote for Postgres because of PostGIS extension that may be handy for travel related site. There's nothing special about your requirements.

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Ruslan Rayanov
Recommends

Hi, Maxim! Most likely, the site is almost ready. But we would like to share our development with you. https://falcon.web-automation.ru/ This is a constructor for web application. With it, you can create almost any site with different roles which have different levels of access to information and different functionality. The platform is managed via sql. knowing sql, you will be able to change the business logic as necessary and during further project maintenance. We will be glad to hear your feedback about the platform.

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Needs advice
on
MongoDBMongoDB
and
MySQLMySQL

Hello, I am developing a new project with an internal chat between users. Also, there are complex relationships between the other project entities but I wolud like to build something scalable and fast and right now I am designing the data model. What kind of database would you recommend me to manage all application data? relational like MySQL, no relational like MongoDB or a mixed one? Thank you

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Replies (6)
Recommends
on
PostgreSQLPostgreSQL

In MongoDB, a write operation is atomic on the level of a single document, so it's harder to deal with consistency without transactions.

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Recommends
on
MongoDBMongoDB

MongoDB supports horizontal scaling through Sharding , distributing data across several machines and facilitating high throughput operations with large sets of data. ... Sharding allows you to add additional instances to increase capacity when required

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Recommends
on
ArangoDBArangoDB

If you are trying with "complex relationships", give a chance to learn ArangoDB and Graph databases. Its database structures allow doing this with faster and simpler queries. The database is not as strict as others and allows arbitrary data. The data model is really like a neural network and you will never need foreign keys tables anymore. In Udemy there is a free course about it to get started.

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Kit Ruparel
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The most important question is where are you planning to host? On-premise, or in the cloud.

Particularly if you are planning to host in either AWS or Azure, then your first point of call should be the PaaS (Platform as a Service) databases supplied by these vendors, as you will find yourself requiring a lot less effort to support them, much easier Disaster Recovery options, and also, depending on how PAYG the database is that you use, potentially also much cheaper costs than having a dedicated database server.

Your question regards 'Relational or not' is obviously key, and you need to consider both your required data structure, as well as the ACID requirements of your application model, as well as the non-functional requirements in terms of scalability, resilience, whether you want security authorisation at the highest application tier, or right down to 'row' level in the database, etc. - however please don't fall into the trap of considering 'NoSQL' as being single category. MongoDB, with its document-store type solution is a very different model to key-value-pair stores (like AWS DynamoDB), or column stores (like AWS RedShift) or for more complex data relationships, Entity Graph Stores (like AWS Neptune), to stores designed for tokenisation and text search (ElasticSearch) etc.

Also critical in all this is how many items you believe you need to index by. RDBMS/SQL stores are great for having as many indexes as you want, other than the slow-down in write speed, whereas databases like Amazon DynamoDB provide blisteringly fast read/write performance, but are very limited on key indexing capabilities.

It feels like you have most experience with SQL/RDBMS technologies, so for the simplest learning curve, and if your application fits it, then I'd personally start by looking at AWS Aurora https://aws.amazon.com/rds/aurora/ .

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Daniel Mwakanema
Software Developer at Kuunika - Data for Action · | 2 upvotes · 634K views
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on
MySQLMySQL

FIrstly, it may help if you explain what you mean by "complex relationships between project entities". Secondly, you can build a fast and scalable solution using either. With that said however, the data sounds relational so I would recommend MySQL.

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R. Tojo
Recommends
on
MySQLMySQL

I think, Its depend of your project type and your skills. MySQL is good and simple for maintenance but MongoDB need more skills and knowledge. If you work on little project, use MySQL. For your project type, MySQL is enough after you can migrate with PostgreSQL

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Prithvi Singh
Application Developer at Montaigne Smart Business Solutions · | 8 upvotes · 906.4K views
Needs advice
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MongoDBMongoDBMySQLMySQL
and
PostgreSQLPostgreSQL

I am going to work on a real estate project and have to decide on a database. Now, SQL databases can be very efficient if appropriately designed. More relations between the data and less redundancy. But with a #NoSQL database, the development time is reduced, and it is easy to query. Since this is my first time working on the real estate domain, I would like to pick a database that would be efficient in the long run.

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Replies (4)
Aric Fedida
Founder, CTO at ASK Technologies Inc · | 15 upvotes · 898.6K views
Recommends
on
PostgreSQLPostgreSQL

I recommend PostgreSQL as it’s the most powerful out of the 3 databases you mentioned. It supports JSON objects so you can mimic the MongoDB functionality, but I would also argue that SQL is actually quite powerful and in many cases significantly easier to work with than with NoSQL databases.

Stay away from foreign keys, keep it fast and simple. Define your data structures well in advance. Try to model your data structures based on your system’s vision; based on where it’s going and not based solely on what you currently need it to do. This will help you avoid drastic changes to your database after your system is launched. Populate the database with fake data and run tests. PostgreSQL allows you to create Views from multiple tables. Try to create those views and make sure you can easily create useful views from multiple tables. Run an Explain on those view queries to make sure you created your indexes correctly. Make sure it’s fast!

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Matthew Rothstein
Recommends
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PostgreSQLPostgreSQL

Any of those three databases are going to be efficient, scalable, and reliable in the long term if you configure and use them correctly. They all also have solid hosting solutions.

All things being equal, I would agree with other posters that Postgres is my preference among the three, but there are caveats.

MongoDB and MySQL have better support for mutli-region replication in your big three cloud environments. Azure recently bought Citus Data, which was a best-in-class Postgres replication solution, so they might be the only one I trust to provide cross-region replication at the moment.

If you have a single region deployment and are on AWS, I can't recommend Aurora Postgres highly enough. It's a very good implementation and extremely performant.

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Josh Dzielak
Co-Founder & CTO at Orbit · | 4 upvotes · 894.1K views
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PostgreSQLPostgreSQL

I'll second another piece of advice. Postgresql's JSON columns are a dream when it comes to productivity and I use them frequently with our Rails application. In these cases, no migration is required to change schema. We store payloads with dozens or hundreds of keys and performance has not been an issue. We also have a lot of relational tables, so the joins we get with SQL are very important to us and hard to replicate with a NoQL solution.

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Danilo Kaltner
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PostgreSQLPostgreSQL

That really depends of where do you see you application in the long run. On any application, any of those choices are excellent. You could argue about good support on JSON binaries, but even MySQL has an excellent support for that on the latest versions.

On the long run, when your application gets hundreds of thousands of requests per second, you might start thinking about how many inputs you will have in the database compared to the outputs. PostgresSQL it’s excellent at giving you outputs, but table corruption can happen when you start receiving this massive number of inputs (Which was the reason Uber switched from Postgres to MySQL)

On our OPS Platform at CTO.ai , we decided to use Postgres, because we need a reliable and agile way to send the output to our users, so that was out best choice in the long run for our product.

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Needs advice
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MSSQLMSSQL
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MySQLMySQL

We are planning to migrate one of my applications from MSSQL to MySQL. Can someone help me with the version to select?. I have a strong inclination towards MySql 5.7. But, I see there are some standout features added in Mysql 8.0 like JSON_TABLE. Just wanted to know if the newer version has not compromised on its speed while giving out some add on features.

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Replies (2)
Rafey Iqbal Rahman
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on
MySQLMySQL
at

MySQL 8.0 is significantly better than MySQL 5.7. For all InnoDB row operations, you'll see a great performance improvement. Also, the time taken to process transactions is lower in MySQL 8.0. Moreover, there has been an improvement in managing read and read/write workloads.

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Jeremy Jones
Digital Developer at SpeakUnique · | 6 upvotes · 290.9K views
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on
MySQLMySQL

MySQL AB doesn't implement anything in MySQL until they can find a way to do it efficiently and, often, more efficiently than other systems. So although I don't have experience with benchmarking JSON_TABLEs or similar new features, their development philosophy alone suggests that version 8 for the latest features would be a safe jump without sacrificing system performance.

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Decisions about MongoDB, MySQL, and PostgreSQL
Usman Sadiq
Student at University of Toronto · | 8 upvotes · 122.8K views
Migrated
from
PostgreSQLPostgreSQL
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MongoDBMongoDB

MongoDB's document-oriented paradigm is nicely suited to the results of our ML model. We felt that this compatibility offered some time savings on figuring out and implementing an extensive data formatting and processing system. MongoDB's flexible schemas schemas (due to it being non-relational) were also attractive as a source of additional agility for our development process. The MongoDB ecosystem also has great GUI tools to simplify testing.

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Backend:

  • Considering that our main app functionality involves data processing, we chose Python as the programming language because it offers many powerful math libraries for data-related tasks. We will use Flask for the server due to its good integration with Python. We will use a relational database because it has good performance and we are mostly dealing with CSV files that have a fixed structure. We originally chose SQLite, but after realizing the limitations of file-based databases, we decided to switch to PostgreSQL, which has better compatibility with our hosting service, Heroku.
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Anthony Simon

I try to follow the 80-20 rule when it comes to my choice of tools. This means my stack consists of about 80% software I already know well, but I do allow myself 20% of the stack to explore tech I have less experience with.

The exact ratio is not what’s important here, it’s more the fact that you should lean towards using proven technologies.

I wrote more about this on my blog post on Choosing Boring Technology: https://panelbear.com/blog/boring-tech/

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Sergey Rodovinsky

At Pushnami we were looking at several alternative databases that would support following architectural requirements: - very quick prototyping for an unknown domain - ability to support large amounts of data - native ability to replicate and fail over - full stack approach for Node.js development After careful consideration MongoDB came on top, and 3 years later we are still very happy with that decision. Currently we keep almost 2TB of data in our cluster, and start thinking about sharding.

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Gabriel Pa

After using couchbase for over 4 years, we migrated to MongoDB and that was the best decision ever! I'm very disappointed with Couchbase's technical performance. Even though we received enterprise support and were a listed Couchbase Partner, the experience was horrible. With every contact, the sales team was trying to get me on a $7k+ license for access to features all other open source NoSQL databases get for free.

Here's why you should not use Couchbase

Full-text search Queries The full-text search often returns a different number of results if you run the same query multiple types

N1QL queries Configuring the indexes correctly is next to impossible. It's poorly documented and nobody seems to know what to do, even the Couchbase support engineers have no clue what they are doing.

Community support I posted several problems on the forum and I never once received a useful answer

Enterprise support It's very expensive. $7k+. The team constantly tried to get me to buy even though the community edition wasn't working great

Autonomous Operator It's actually just a poorly configured Kubernetes role that no matter what I did, I couldn't get it to work. The support team was useless. Same lack of documentation. If you do get it to work, you need 6 servers at least to meet their minimum requirements.

Couchbase cloud Typical for Couchbase, the user experience is awful and I could never get it to work.

Minimum requirements The minimum requirements in production are 6 servers. On AWS the calculated monthly cost would be ~$600. We achieved better performance using a $16 MongoDB instance on the Mongo Atlas Cloud

writing queries is a nightmare While N1QL is similar to SQL and it's easier to write because of the familiarity, that isn't entirely true. The "smart index" that Couchbase advertises is not smart at all. Creating an index with 5 fields, and only using 4 of them won't result in Couchbase using the same index, so you have to create a new one.

Couchbase UI The UI that comes with every database deployment is full of bugs, barely functional and the developer experience is poor. When I asked Couchbase about it, they basically said they don't care because real developers use SQL directly from code

Consumes too much RAM Couchbase is shipped with a smaller Memcached instance to handle the in-memory cache. Memcached ends up using 8 GB of RAM for 5000 documents! I'm not kidding! We had less than 5000 docs on a Couchbase instance and less than 20 indexes and RAM consumption was always over 8 GB

Memory allocations are useless I asked the Couchbase team a question: If a bucket has 1 GB allocated, what happens when I have more than 1GB stored? Does it overflow? Does it cache somewhere? Do I get an error? I always received the same answer: If you buy the Couchbase enterprise then we can guide you.

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Daniel Moya
Data Engineer at Dimensigon · | 4 upvotes · 455.8K views

We have chosen Tibero over Oracle because we want to offer a PL/SQL-as-a-Service that the users can deploy in any Cloud without concerns from our website at some standard cost. With Oracle Database, developers would have to worry about what they implement and the related costs of each feature but the licensing model from Tibero is just 1 price and we have all features included, so we don't have to worry and developers using our SQLaaS neither. PostgreSQL would be open source. We have chosen Tibero over Oracle because we want to offer a PL/SQL that you can deploy in any Cloud without concerns. PostgreSQL would be the open source option but we need to offer an SQLaaS with encryption and more enterprise features in the background and best value option we have found, it was Tibero Database for PL/SQL-based applications.

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Omran Jamal
CTO & Co-founder at Bonton Connect · | 4 upvotes · 549.8K views

We actually use both Mongo and SQL databases in production. Mongo excels in both speed and developer friendliness when it comes to geospatial data and queries on the geospatial data, but we also like ACID compliance hence most of our other data (except on-site logs) are stored in a SQL Database (MariaDB for now)

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Tom Klein

The Gentlent Tech Team made lots of updates within the past year. The biggest one being our database:

We decided to migrate our #PostgreSQL -based database systems to a custom implementation of #Cassandra . This allows us to integrate our product data perfectly in a system that just makes sense. High availability and scalability are supported out of the box.

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Kyle Harrison
Web Application Developer at Fortinet · | 11 upvotes · 964.8K views

MySQL has a lot of strengths working for it. It's simple and easy to set up and use. It's JSON engine is also really good these days. Mongo is also simple to setup and use, and it's speed as a document-object storage engine is first class.

Where Postgres has both beat is in it's combining of all of the features that make both MySQL and Mongo great, while adding on enterprise grade level scalability and replication. It's Postgres' stability and robustness, while still fulfilling the roles of it's contemporaries extremely well that edge Postgre for me.

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When I was new with web development, I was using PHP for backend and MySQL for database. But after improving my JS skills, I chosen Node.js. Because of too many reasons including npm, express, community, fast coding and etc. MongoDB is so good for using with Node.js. If your JS skills are enough good, I recommend to migrate to Node.js and MongoDB.

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Pros of MongoDB
Pros of MySQL
Pros of PostgreSQL
  • 827
    Document-oriented storage
  • 593
    No sql
  • 553
    Ease of use
  • 464
    Fast
  • 410
    High performance
  • 255
    Free
  • 218
    Open source
  • 180
    Flexible
  • 145
    Replication & high availability
  • 112
    Easy to maintain
  • 42
    Querying
  • 39
    Easy scalability
  • 38
    Auto-sharding
  • 37
    High availability
  • 31
    Map/reduce
  • 27
    Document database
  • 25
    Easy setup
  • 25
    Full index support
  • 16
    Reliable
  • 15
    Fast in-place updates
  • 14
    Agile programming, flexible, fast
  • 12
    No database migrations
  • 8
    Easy integration with Node.Js
  • 8
    Enterprise
  • 6
    Enterprise Support
  • 5
    Great NoSQL DB
  • 4
    Support for many languages through different drivers
  • 3
    Schemaless
  • 3
    Aggregation Framework
  • 3
    Drivers support is good
  • 2
    Fast
  • 2
    Managed service
  • 2
    Easy to Scale
  • 2
    Awesome
  • 2
    Consistent
  • 1
    Good GUI
  • 1
    Acid Compliant
  • 800
    Sql
  • 679
    Free
  • 562
    Easy
  • 528
    Widely used
  • 490
    Open source
  • 180
    High availability
  • 160
    Cross-platform support
  • 104
    Great community
  • 79
    Secure
  • 75
    Full-text indexing and searching
  • 26
    Fast, open, available
  • 16
    Reliable
  • 16
    SSL support
  • 15
    Robust
  • 9
    Enterprise Version
  • 7
    Easy to set up on all platforms
  • 3
    NoSQL access to JSON data type
  • 1
    Relational database
  • 1
    Easy, light, scalable
  • 1
    Sequel Pro (best SQL GUI)
  • 1
    Replica Support
  • 763
    Relational database
  • 510
    High availability
  • 439
    Enterprise class database
  • 383
    Sql
  • 304
    Sql + nosql
  • 173
    Great community
  • 147
    Easy to setup
  • 131
    Heroku
  • 130
    Secure by default
  • 113
    Postgis
  • 50
    Supports Key-Value
  • 48
    Great JSON support
  • 34
    Cross platform
  • 33
    Extensible
  • 28
    Replication
  • 26
    Triggers
  • 23
    Multiversion concurrency control
  • 23
    Rollback
  • 21
    Open source
  • 18
    Heroku Add-on
  • 17
    Stable, Simple and Good Performance
  • 15
    Powerful
  • 13
    Lets be serious, what other SQL DB would you go for?
  • 11
    Good documentation
  • 9
    Scalable
  • 8
    Free
  • 8
    Reliable
  • 8
    Intelligent optimizer
  • 7
    Transactional DDL
  • 7
    Modern
  • 6
    One stop solution for all things sql no matter the os
  • 5
    Relational database with MVCC
  • 5
    Faster Development
  • 4
    Full-Text Search
  • 4
    Developer friendly
  • 3
    Excellent source code
  • 3
    Free version
  • 3
    Great DB for Transactional system or Application
  • 3
    Relational datanbase
  • 3
    search
  • 3
    Open-source
  • 2
    Text
  • 2
    Full-text
  • 1
    Can handle up to petabytes worth of size
  • 1
    Composability
  • 1
    Multiple procedural languages supported
  • 0
    Native

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Cons of MongoDB
Cons of MySQL
Cons of PostgreSQL
  • 6
    Very slowly for connected models that require joins
  • 3
    Not acid compliant
  • 2
    Proprietary query language
  • 16
    Owned by a company with their own agenda
  • 3
    Can't roll back schema changes
  • 10
    Table/index bloatings

Sign up to add or upvote consMake informed product decisions

What is MongoDB?

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

What is MySQL?

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

What is PostgreSQL?

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

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Blog Posts

Dec 22 2021 at 5:41AM

Pinterest

MySQLKafkaDruid+3
3
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Dec 8 2020 at 5:50PM

DigitalOcean

GitHubMySQLPostgreSQL+11
3
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MySQLKafkaApache Spark+6
4
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Nov 20 2019 at 3:38AM

OneSignal

PostgreSQLRedisRuby+8
9
4703
What are some alternatives to MongoDB, MySQL, and PostgreSQL?
Amazon DynamoDB
With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.
Couchbase
Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.
Cassandra
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
Elasticsearch
Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
Neo4j
Neo4j stores data in nodes connected by directed, typed relationships with properties on both, also known as a Property Graph. It is a high performance graph store with all the features expected of a mature and robust database, like a friendly query language and ACID transactions.
See all alternatives