MariaDB vs Oracle

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MariaDB vs Oracle: What are the differences?

Introduction

MariaDB and Oracle are both popular relational database management systems (RDBMS) with their own sets of features and capabilities. While they share some similarities, there are key differences between the two.

  1. Scalability: One major difference between MariaDB and Oracle is their scalability. Oracle offers robust scalability options, allowing for easy scaling of both hardware and software resources, making it well-suited for enterprise-level applications with high traffic and extensive data requirements. On the other hand, MariaDB also provides scalability features but may not be as comprehensive as Oracle's offerings, making it a better choice for small to medium-sized applications.

  2. Licensing: Another significant difference lies in their licensing models. MariaDB is an open-source RDBMS, released under the GNU General Public License (GPL), which means it is free to use and modify. Oracle, on the other hand, is a commercial RDBMS that requires a paid license for most use cases. This distinction can have cost implications for organizations, especially those with budget limitations.

  3. Replication: Replication, the ability to create copies of data and distribute it to multiple database instances, is vital for high availability and data redundancy. Oracle offers advanced replication features, providing various options for replication topologies and synchronization methods. MariaDB also supports replication but may have fewer options and features compared to Oracle. Organizations with complex replication requirements may prefer Oracle for its robust capabilities.

  4. Enterprise features: As a commercial RDBMS, Oracle tends to have a broader range of enterprise-grade features compared to MariaDB. These features include advanced security options, comprehensive backup and recovery mechanisms, advanced analytics, and high availability options. While MariaDB offers similar functionality, it may lack some of the more advanced or specialized features found in Oracle.

  5. Ecosystem and support: Oracle has been a dominant player in the RDBMS market for a long time, resulting in a mature ecosystem and extensive support options. The availability of certified professionals, third-party tools, and documentation is abundant for Oracle. Although MariaDB has gained significant popularity since its inception, it may have a relatively smaller ecosystem by comparison, which could impact the availability of specialized support or third-party integrations.

  6. Compatibility and standardization: Both MariaDB and Oracle adhere to SQL standards and provide SQL compatibility. However, Oracle has historically placed a stronger emphasis on adhering to standards and has implemented more SQL-related features, making it more compliant. Adhering closely to standards can simplify migration and interoperability with other database systems.

Summary

In summary, the key differences between MariaDB and Oracle lie in their scalability options, licensing models, replication features, enterprise-grade functionality, ecosystem and support, as well as compatibility with SQL standards. These factors should be considered when choosing a database management system that best fits the specific requirements of an organization or application.

Advice on MariaDB and Oracle
Maxim Ryakhovskiy
Needs advice
on
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 · 213.7K 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 · 206K 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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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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Václav Hodek
CEO, lead developer at Localazy · | 1 upvotes · 206.4K 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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Decisions about MariaDB and Oracle
Daniel Moya
Data Engineer at Dimensigon · | 4 upvotes · 422.4K 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 · 518.7K 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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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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Pros of MariaDB
Pros of Oracle
  • 149
    Drop-in mysql replacement
  • 100
    Great performance
  • 74
    Open source
  • 55
    Free
  • 44
    Easy setup
  • 15
    Easy and fast
  • 14
    Lead developer is "monty" widenius the founder of mysql
  • 6
    Also an aws rds service
  • 4
    Consistent and robust
  • 4
    Learning curve easy
  • 2
    Native JSON Support / Dynamic Columns
  • 1
    Real Multi Threaded queries on a table/db
  • 44
    Reliable
  • 33
    Enterprise
  • 15
    High Availability
  • 5
    Expensive
  • 5
    Hard to maintain
  • 4
    Maintainable
  • 4
    Hard to use
  • 3
    High complexity

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Cons of MariaDB
Cons of Oracle
    Be the first to leave a con
    • 14
      Expensive

    Sign up to add or upvote consMake informed product decisions

    - No public GitHub repository available -

    What is 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.

    What is 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.

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    What companies use MariaDB?
    What companies use Oracle?
    See which teams inside your own company are using MariaDB or Oracle.
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    What are some alternatives to MariaDB and Oracle?
    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.
    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.
    Percona
    It delivers enterprise-class software, support, consulting and managed services for both MySQL and MongoDB across traditional and cloud-based platforms.
    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.
    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.
    See all alternatives