MariaDB is an open-source relational database made by the original developers of MySQL, supported by the MariaDB Foundation and a community of developers. The community states recent additional capabilities as including clustering with Galera Cluster 4, compatibility with Oracle Database, and Temporal Data Tables, allowing one to query the data as it stood at any point in the past.
N/A
MongoDB
Score 8.6 out of 10
N/A
MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
$0
per month
Pricing
MariaDB Platform
MongoDB
Editions & Modules
No answers on this topic
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Offerings
Pricing Offerings
MariaDB Platform
MongoDB
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
Optional
No setup fee
Additional Details
—
Fully managed, global cloud database on AWS, Azure, and GCP
More Pricing Information
Community Pulse
MariaDB Platform
MongoDB
Features
MariaDB Platform
MongoDB
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Our installation scenario is a MariaDB cluster composed of 3 nodes to achieve high availability in the service and in this way the application that accesses the backend (MariaDB) is always working and is not down at any time.
To achieve high performance of the application when accessing the database, a MariaDB MaxScale has been mounted that acts as a proxy for queries to the database.
MongoDB [is] great at storing JSON data grouped into "collections". In this format, you can store any JSON documents and conveniently categorize them by collections. The JSON document contained in MongoDB is called binary JSON or BSON and, like any other document in this format, is unstructured. Therefore, unlike traditional DBMS, any kind of data can be stored in collections, and this flexibility is combined with the horizontal scalability of the database. It should be noted that MongoDB does not have links between documents and “collections” (this is partially compensated by the Database Reference - links in the DBMS, but this does not completely solve the problem). As a result, a situation arises in which there is a certain set of data that is not related to other information in the database, and there is no way to combine data from different documents. In SQL systems, this would be an elementary task.
MariaDB does well with PHP or Python (django) in a web environment. Developers are able to work quickly.
MariaDB is extremely well documented and has a gigantic support community. If you need ask a question on how to do things you can go to many placces online and find answers quickly.
MariaDB is fast! Queries with tens of thousands of rows are quick.
MariaDB is highly compatible with Oracle's MySQL. Basically the same thing but more open and with a brighter future.
With MariaDB it is so easy to import and export data, and backups are a cinch. This saves me so much time as compared to other RDBMS.
Easy to learn. When I picked up MongoDB for the first time, I had little background in database management or modeling. If you have a background in javascript (and JSON)... then you can figure out how to use MongoDB pretty fast.
Fast performance.
It's relatively easy to set up in certain environments because there are lots of ready-made solutions out there.
There's a lot of support in the existing ecosystem for it —, especially in the node.js realm.
Query syntax is pretty simple to grasp and utilize.
Aggregate functions are powerful.
Scaling options.
Documentation is quite good and versioned for each release.
Driver Support - Some third party applications use database drivers that cause unexplained slowness with MariaDB. This can be worked around by using the MySQL drivers, but it's not clear what causes the problem in the first place.
Support - While online communities are helpful in diagnosing problems, there isn't as much professional documentation/support available for MariaDB as some of the other major database options.
Data Visualization - It would be helpful if there were more built in options for analyzing statistics and generating reports.
MongoDB is one of the most famous non-relational databases in the world, there are famous active projects that use this database. I think that the same company that develops the database gives you the online induction totally free is something that really is very positive. Accounts with a first-class support to be able to relate the correct implementation of the database, in addition to teaching you the best practices to optimize your projects, I believe that with this decision it is more than obvious which is the best decision at the time of seeing with which database to work.
MariaDB is very usable and stable to be used in production settings as an alternative to MySQL. The shortcomings of SQL are present but well understood in the community, and if the decision were to be made again, I would choose MariaDB over MySQL on future projects.
It is one of the reasons why we prefer it to store documents in a JSON-style format, to access the desired document very quickly regardless of its size, to be readable by human eyes, and to be easily scalable and manageable.
Yes, I would recommend MariaDB Platform support because they answer very fast and with detailed information. They also help you with the design of the storage infrastructure, not only with the maintenance problems. On the other hand, this service is a bit expensive.
I have reached multiple times to the MongoDB community for the help and they have provided each and easy solution for every problem. Over the internet and on stack overflow many people responds over the challenges. Now this tool is very much used in every company and projects so internally many people are there to give a support.
While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
It did not always compete against these technologies. Most of the time, it was complementing these databases for certain use cases to help provide a much more complete database. This makes more users want to use it to explore new solutions that help users. This is our target and how [we] work with MariaDb.
The environment I work in is somewhat unique in that we use both MySQL and MongoDB. However, each is used for specific purposes that the other is not well suited for. MongoDB is not a relational database like MySQL, so it serves as the perfect place to dump key bits of data for quick retrieval later. This is something we can't easily do with MySQL. On this smaller database, MongoDB also lets us retrieve data more quickly with its fast and efficient querying.
MariaDB has saved us enormously on licensing compared to our previous DB software vendor.
In service, it has enabled us (speaking as the internal DB team here) to provide better service to the other teams in the company as well as our customers, with less staff.
The level of hardware required for adequate performance, in our environment, has been much lower. Those savings have been substantial, above and beyond savings on licensing and DBA staffing levels.
We can make more open and flexible systems due to its easy adaptation to new evolutions in web applications.
In the latest versions it offers support for different transactions and we could carry out real tests related to the concurrency of the application.
MongoDB allows you to have distributed clusters, which improves the speed of the queries by reducing the latency that exists between the database cluster and the service that executes the query.
