MySQL vs TimescaleDB

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MySQL vs TimescaleDB: What are the differences?

Introduction

TimescaleDB is an open-source relational database management system designed to handle time-series data. It is built on top of PostgreSQL and provides enhanced scalability and performance for time-series workloads. In comparison, MySQL is a popular open-source relational database management system that offers comprehensive features and support for various applications.

  1. Architecture: MySQL follows a traditional RDBMS architecture, while TimescaleDB extends PostgreSQL's architecture to support time-series data efficiently. TimescaleDB introduces hypertables, a partitioning mechanism that enables time-based partitioning of data for optimal query performance.

  2. Scalability: MySQL can horizontally scale using replication and sharding techniques, but it requires additional effort and maintenance. TimescaleDB, on the other hand, comes with built-in automatic data partitioning and parallel query processing, allowing for seamless scalability.

  3. Compression: TimescaleDB provides built-in time-series data compression techniques, including delta compression and run-length encoding. This compression reduces storage requirements and improves query performance. MySQL does not offer native compression for time-series data.

  4. Continuous Aggregations: TimescaleDB supports continuous aggregations, which allow users to precompute and store aggregated results. This feature significantly speeds up queries that require aggregations over large time-series datasets. MySQL does not have native support for continuous aggregations.

  5. Data Retention Policies: TimescaleDB offers data retention policies that allow automatic removal of old data based on criteria such as time or size. This feature simplifies data lifecycle management for time-series data. MySQL requires manual intervention or custom scripts to implement similar functionality.

  6. Time-Series Specific Functions: TimescaleDB provides several time-series-specific functions and operators, such as timebucket, timebucketgapfill, and timebucket_overlap. These functions simplify time-series data manipulation and analysis. While MySQL offers some date and time functions, it lacks dedicated functions for time-series analysis.

In summary, TimescaleDB extends PostgreSQL with features specific to time-series data management, such as optimized partitioning, built-in compression, continuous aggregations, and data retention policies. MySQL is a generic RDBMS that requires additional effort to handle time-series data effectively.

Advice on MySQL and TimescaleDB
Needs advice
on
MongoDBMongoDBMySQLMySQL
and
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 · 170.7K 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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Umair Iftikhar
Technical Architect at ERP Studio · | 3 upvotes · 433.1K views
Needs advice
on
CassandraCassandraDruidDruid
and
TimescaleDBTimescaleDB

Developing a solution that collects Telemetry Data from different devices, nearly 1000 devices minimum and maximum 12000. Each device is sending 2 packets in 1 second. This is time-series data, and this data definition and different reports are saved on PostgreSQL. Like Building information, maintenance records, etc. I want to know about the best solution. This data is required for Math and ML to run different algorithms. Also, data is raw without definitions and information stored in PostgreSQL. Initially, I went with TimescaleDB due to PostgreSQL support, but to increase in sites, I started facing many issues with timescale DB in terms of flexibility of storing data.

My major requirement is also the replication of the database for reporting and different purposes. You may also suggest other options other than Druid and Cassandra. But an open source solution is appreciated.

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Replies (1)
Recommends
on
MongoDBMongoDB

Hi Umair, Did you try MongoDB. We are using MongoDB on a production environment and collecting data from devices like your scenario. We have a MongoDB cluster with three replicas. Data from devices are being written to the master node and real-time dashboard UI is using the secondary nodes for read operations. With this setup write operations are not affected by read operations too.

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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 · 265.9K 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 · 257.4K 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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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
Recommends
on
Apache AuroraApache Aurora

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 · 593.3K views
Recommends
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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RODIALSON Tojo
FullStack Developer / CTO at O2Development · | 2 upvotes · 593.7K views
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 · 845.9K views
Needs advice
on
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 · 838K 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
on
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 · 833.5K views
Recommends
on
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
Recommends
on
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
on
MSSQLMSSQL
and
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)
Jeremy Jones
Digital Developer at SpeakUnique · | 6 upvotes · 268.4K views
Recommends
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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Rafey Iqbal Rahman
Cofounder at Wanderloop · | 6 upvotes · 269K views
Recommends
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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Needs advice
on
MongoDBMongoDBMySQLMySQL
and
PostgreSQLPostgreSQL

Hello,

I am trying to design an online ordering app similar to Doordash or Uber Eats. I'm having a hard time trying to finalise on what database (or mixture of databases) to use. I'm leaning towards using a relational database like MySQL or PostgreSQL. But, when the application grows, I don't want to join on 20 tables to get a data. Any help would be greatly appreciated. Thank you for your time.

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Replies (2)
Rupen Makhecha
Recommends
on
MySQLMySQL

Hello Suhas , We build our product www.voilacabs.com which is in the same lines as yours but we have used a combination of Mysql and MongoDB. When using MySQL, i would recommend doing the following: 1. Use Mysql only for storage only and for realtime updates we recommend MongoDB. 2. Don't try to Join more than 3 tables. ( the moment you reach 3 join stop there and try to un-normalized database. 3. Never or very rarely use Auto-increments. ( we recommend using UUIDS ) . Use UUIDS always for Auto increments for MYSQL. If you using Postgre SQL then i would suggest you to please check this https://instagram-engineering.com/sharding-ids-at-instagram-1cf5a71e5a5c There is a stored procedure that generated unique keys instead of auto-increment keys and that will help you sharding or clustering database without sync errors. 4. Also For MongoDB if you can put a layer of REDIS Cache then that will boost your api performance under large loads. 5. Use Node.js programing language as that function asynchronously .

Let me know if you still need any suggestion's . Thanks & Regards Rupen Makhecha CTO @ Voila Cab's www.voilacabs.com

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Rafey Iqbal Rahman
Recommends
on
MySQLMySQL
at

I would recommend a mixture of MySQL and MongoDB. Using MongoDB for the Content Distribution Network (CDN) will make it easy to store high volume incoming data. MySQL is recommended to be used for business logic. PostgreSQL is not recommended since you will be faced with inefficient database replication features and constant migration from one PostgreSQL version to another.

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Needs advice
on
InfluxDBInfluxDBMongoDBMongoDB
and
TimescaleDBTimescaleDB

We are building an IOT service with heavy write throughput and fewer reads (we need downsampling records). We prefer to have good reliability when comes to data and prefer to have data retention based on policies.

So, we are looking for what is the best underlying DB for ingesting a lot of data and do queries easily

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Replies (3)
Yaron Lavi
Recommends
on
PostgreSQLPostgreSQL

We had a similar challenge. We started with DynamoDB, Timescale, and even InfluxDB and Mongo - to eventually settle with PostgreSQL. Assuming the inbound data pipeline in queued (for example, Kinesis/Kafka -> S3 -> and some Lambda functions), PostgreSQL gave us a We had a similar challenge. We started with DynamoDB, Timescale and even InfluxDB and Mongo - to eventually settle with PostgreSQL. Assuming the inbound data pipeline in queued (for example, Kinesis/Kafka -> S3 -> and some Lambda functions), PostgreSQL gave us better performance by far.

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Recommends
on
DruidDruid

Druid is amazing for this use case and is a cloud-native solution that can be deployed on any cloud infrastructure or on Kubernetes. - Easy to scale horizontally - Column Oriented Database - SQL to query data - Streaming and Batch Ingestion - Native search indexes It has feature to work as TimeSeriesDB, Datawarehouse, and has Time-optimized partitioning.

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Ankit Malik
Software Developer at CloudCover · | 3 upvotes · 320.3K views
Recommends
on
Google BigQueryGoogle BigQuery

if you want to find a serverless solution with capability of a lot of storage and SQL kind of capability then google bigquery is the best solution for that.

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Navraj Chohan
Needs advice
on
MySQLMySQL
and
PostgreSQLPostgreSQL

I asked my last question incorrectly. Rephrasing it here.

I am looking for the most secure open source database for my project I'm starting: https://github.com/SuPragma/SuPragma/wiki

Which database is more secure? MySQL or PostgreSQL? Are there others I should be considering? Is it possible to change the encryption keys dynamically?

Thanks,

Raj

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Replies (2)
Pierrick Martos
Engineering Manager at Akeneo · | 4 upvotes · 329.1K views
Recommends
on
PostgreSQLPostgreSQL

PostgreSQL provides more tools and builtin features around security, eg: row level security and the support of SELinux (through SE-PostgreSQL). Overall, whatever you choose, the important is to keep it updated and have the skills to apply security best practices and update them regurarly, without this, it's like putting your money in Fort knox but leaving the vault key in a public place.

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Umair Iftikhar
Technical Architect at ERP Studio · | 4 upvotes · 329.1K views
Recommends
on
PostgreSQLPostgreSQL

It is open-source and more tools than mySQL. PostgreSQL is an object-relational database management system (ORDBMS) with an emphasis on extensibility and standards compliance. It is also good for small companies due to tools for free availability. PostgreSQL includes built-in support for regular B-tree and hash indexes. Indexes in PostgreSQL also support Expression & Partial Indices ( index only a part of a table). Expression Index can be created with an index of the result of an expression or function, instead of simply the value of a column.

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I am a Microsoft SQL Server programmer who is a bit out of practice. I have been asked to assist on a new project. The overall purpose is to organize a large number of recordings so that they can be searched. I have an enormous music library but my songs are several hours long. I need to include things like time, date and location of the recording. I don't have a problem with the general database design. I have two primary questions:

  1. I need to use either MySQL or PostgreSQL on a Linux based OS. Which would be better for this application?
  2. I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.
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Replies (6)

Hi Erin,

Honestly both databases will do the job just fine. I personally prefer Postgres.

Much more important is how you store the audio. While you could technically use a blob type column, it's really not ideal to be storing audio files which are "several hours long" in a database row. Instead consider storing the audio files in an object store (hosted options include backblaze b2 or aws s3) and persisting the key (which references that object) in your database column.

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Aaron Westley
Recommends
on
PostgreSQLPostgreSQL

Hi Erin, Chances are you would want to store the files in a blob type. Both MySQL and Postgres support this. Can you explain a little more about your need to store the files in the database? I may be more effective to store the files on a file system or something like S3. To answer your qustion based on what you are descibing I would slighly lean towards PostgreSQL since it tends to be a little better on the data warehousing side.

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Christopher Wray
Web Developer at Soltech LLC · | 3 upvotes · 426.4K views
Recommends
on
DirectusDirectus
at

Hey Erin! I would recommend checking out Directus before you start work on building your own app for them. I just stumbled upon it, and so far extremely happy with the functionalities. If your client is just looking for a simple web app for their own data, then Directus may be a great option. It offers "database mirroring", so that you can connect it to any database and set up functionality around it!

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Julien DeFrance
Principal Software Engineer at Tophatter · | 3 upvotes · 426K views
Recommends
on
Amazon AuroraAmazon Aurora

Hi Erin! First of all, you'd probably want to go with a managed service. Don't spin up your own MySQL installation on your own Linux box. If you are on AWS, thet have different offerings for database services. Standard RDS vs. Aurora. Aurora would be my preferred choice given the benefits it offers, storage optimizations it comes with... etc. Such managed services easily allow you to apply new security patches and upgrades, set up backups, replication... etc. Doing this on your own would either be risky, inefficient, or you might just give up. As far as which database to chose, you'll have the choice between Postgresql, MySQL, Maria DB, SQL Server... etc. I personally would recommend MySQL (latest version available), as the official tooling for it (MySQL Workbench) is great, stable, and moreover free. Other database services exist, I'd recommend you also explore Dynamo DB.

Regardless, you'd certainly only keep high-level records, meta data in Database, and the actual files, most-likely in S3, so that you can keep all options open in terms of what you'll do with them.

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Recommends
on
PostgreSQLPostgreSQL

Hi Erin,

  • Coming from "Big" DB engines, such as Oracle or MSSQL, go for PostgreSQL. You'll get all the features you need with PostgreSQL.
  • Your case seems to point to a "NoSQL" or Document Database use case. Since you get covered on this with PostgreSQL which achieves excellent performances on JSON based objects, this is a second reason to choose PostgreSQL. MongoDB might be an excellent option as well if you need "sharding" and excellent map-reduce mechanisms for very massive data sets. You really should investigate the NoSQL option for your use case.
  • Starting with AWS Aurora is an excellent advise. since "vendor lock-in" is limited, but I did not check for JSON based object / NoSQL features.
  • If you stick to Linux server, the PostgreSQL or MySQL provided with your distribution are straightforward to install (i.e. apt install postgresql). For PostgreSQL, make sure you're comfortable with the pg_hba.conf, especially for IP restrictions & accesses.

Regards,

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Klaus Nji
Staff Software Engineer at SailPoint Technologies · | 1 upvotes · 426K views
Recommends
on
PostgreSQLPostgreSQL

I recommend Postgres as well. Superior performance overall and a more robust architecture.

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Decisions about MySQL and TimescaleDB
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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Kyle Harrison
Web Application Developer at Fortinet · | 11 upvotes · 902.5K 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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David Österreicher

Easier scalability of MongoDB prompted this migration from MySQL.

As Runtastic grew, at some point it would have outgrown our MySQL installation. We looked for a couple of alternatives and found MongoDB as a great replacement for our use case. Read how a migration of live data from one database to another worked for us.

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Chose
MongoDBMongoDB
over
MySQLMySQL

My data was inherently hierarchical, but there was not enough content in each level of the hierarchy to justify a relational DB (SQL) with a one-to-many approach. It was also far easier to share data between the frontend (Angular), backend (Node.js) and DB (MongoDB) as they all pass around JSON natively. This allowed me to skip the translation layer from relational to hierarchical. You do need to think about correct indexes in MongoDB, and make sure the objects have finite size. For instance, an object in your DB shouldn't have a property which is an array that grows over time, without limit. In addition, I did use MySQL for other types of data, such as a catalog of products which (a) has a lot of data, (b) flat and not hierarchical, (c) needed very fast queries.

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Ram Kumar
CTO, Architect at Sarvasv.in · | 2 upvotes · 408.8K views

PostgreSQL is enterprise level database with transactions, full-text indexes, vector indexes, JSON, BLOB, geo-spatial data and a lot more. Highly scalable, configurable and easily maintainable. all that on an open source RDBMS database and you are still looking for GPL licensed MySQL with limited features? Look again.

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We wanted a JSON datastore that could save the state of our bioinformatics visualizations without destructive normalization. As a leading NoSQL data storage technology, MongoDB has been a perfect fit for our needs. Plus it's open source, and has an enterprise SLA scale-out path, with support of hosted solutions like Atlas. Mongo has been an absolute champ. So much so that SQL and Oracle have begun shipping JSON column types as a new feature for their databases. And when Fast Healthcare Interoperability Resources (FHIR) announced support for JSON, we basically had our FHIR datalake technology.

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In the field of bioinformatics, we regularly work with hierarchical and unstructured document data. Unstructured text data from PDFs, image data from radiographs, phylogenetic trees and cladograms, network graphs, streaming ECG data... none of it fits into a traditional SQL database particularly well. As such, we prefer to use document oriented databases.

MongoDB is probably the oldest component in our stack besides Javascript, having been in it for over 5 years. At the time, we were looking for a technology that could simply cache our data visualization state (stored in JSON) in a database as-is without any destructive normalization. MongoDB was the perfect tool; and has been exceeding expectations ever since.

Trivia fact: some of the earliest electronic medical records (EMRs) used a document oriented database called MUMPS as early as the 1960s, prior to the invention of SQL. MUMPS is still in use today in systems like Epic and VistA, and stores upwards of 40% of all medical records at hospitals. So, we saw MongoDB as something as a 21st century version of the MUMPS database.

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Kyle Harrison
Web Application Developer at Fortinet · | 21 upvotes · 367.7K views

While there's been some very clever techniques that has allowed non-natively supported geo querying to be performed, it is incredibly slow in the long game and error prone at best.

MySQL finally introduced it's own GEO functions and special indexing operations for GIS type data. I prototyped with this, as MySQL is the most familiar database to me. But no matter what I did with it, how much tuning i'd give it, how much I played with it, the results would come back inconsistent.

It was very disappointing.

I figured, at this point, that SQL Server, being an enterprise solution authored by one of the biggest worldwide software developers in the world, Microsoft, might contain some decent GIS in it.

I was very disappointed.

Postgres is a Database solution i'm still getting familiar with, but I noticed it had no built in support for GIS. So I hilariously didn't pay it too much attention. That was until I stumbled upon PostGIS and my world changed forever.

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I happen to point my asp.net core web application from MSSQL to MySQL due to infrastructure costs associated with the former db. The application also had challenges creating a migration schema of asp.net membership on MySQL.

After a thorough research I figured out how to do it and also made a video and uploaded to youtube. You can check that here https://youtu.be/X4I0DUw6C84

The full source code for the demo template is available on github here http://bit.ly/2LWgacA

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Pros of MySQL
Pros of TimescaleDB
  • 800
    Sql
  • 679
    Free
  • 562
    Easy
  • 528
    Widely used
  • 489
    Open source
  • 180
    High availability
  • 160
    Cross-platform support
  • 104
    Great community
  • 78
    Secure
  • 75
    Full-text indexing and searching
  • 25
    Fast, open, available
  • 16
    SSL support
  • 15
    Reliable
  • 14
    Robust
  • 8
    Enterprise Version
  • 7
    Easy to set up on all platforms
  • 2
    NoSQL access to JSON data type
  • 1
    Relational database
  • 1
    Easy, light, scalable
  • 1
    Sequel Pro (best SQL GUI)
  • 1
    Replica Support
  • 9
    Open source
  • 8
    Easy Query Language
  • 7
    Time-series data analysis
  • 5
    Established postgresql API and support
  • 4
    Reliable
  • 2
    Paid support for automatic Retention Policy
  • 2
    Chunk-based compression
  • 2
    Postgres integration
  • 2
    High-performance
  • 2
    Fast and scalable
  • 1
    Case studies

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Cons of MySQL
Cons of TimescaleDB
  • 16
    Owned by a company with their own agenda
  • 3
    Can't roll back schema changes
  • 5
    Licensing issues when running on managed databases

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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 TimescaleDB?

TimescaleDB: An open-source database built for analyzing time-series data with the power and convenience of SQL — on premise, at the edge, or in the cloud.

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What companies use MySQL?
What companies use TimescaleDB?
See which teams inside your own company are using MySQL or TimescaleDB.
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What tools integrate with MySQL?
What tools integrate with TimescaleDB?

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Blog Posts

Dec 22 2021 at 5:41AM

Pinterest

MySQLKafkaDruid+3
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Dec 8 2020 at 5:50PM

DigitalOcean

GitHubMySQLPostgreSQL+11
2
2352
MySQLKafkaApache Spark+6
2
1999
GitHubDockerReact+17
40
36150
What are some alternatives to MySQL and TimescaleDB?
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.
Oracle
Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
MariaDB
Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.
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.
Microsoft SQL Server
Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.
See all alternatives