MariaDB vs MongoDB vs MySQL

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Decisions about MariaDB, MongoDB, and MySQL
Sergey Rodovinsky

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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Omran Jamal
CTO & Co-founder at Bonton Connect · | 4 upvotes · 122.8K 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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Pros of MariaDB
Pros of MongoDB
Pros of MySQL
  • 149
    Drop-in mysql replacement
  • 101
    Great performance
  • 74
    Open source
  • 56
  • 45
    Easy setup
  • 16
    Easy and fast
  • 14
    Lead developer is "monty" widenius the founder of mysql
  • 6
    Also an aws rds service
  • 4
    Learning curve easy
  • 4
    Consistent and robust
  • 1
    Native JSON Support / Dynamic Columns
  • 822
    Document-oriented storage
  • 585
    No sql
  • 544
    Ease of use
  • 462
  • 404
    High performance
  • 251
  • 212
    Open source
  • 177
  • 139
    Replication & high availability
  • 107
    Easy to maintain
  • 39
  • 35
    Easy scalability
  • 34
  • 33
    High availability
  • 29
  • 26
    Document database
  • 24
    Full index support
  • 24
    Easy setup
  • 15
  • 14
    Fast in-place updates
  • 13
    Agile programming, flexible, fast
  • 11
    No database migrations
  • 7
    Easy integration with Node.Js
  • 7
  • 5
    Enterprise Support
  • 4
    Great NoSQL DB
  • 3
    Support for many languages through different drivers
  • 3
    Aggregation Framework
  • 3
    Drivers support is good
  • 2
    Easy to Scale
  • 2
  • 2
  • 2
  • 2
    Managed service
  • 1
  • 789
  • 674
  • 557
  • 527
    Widely used
  • 485
    Open source
  • 180
    High availability
  • 158
    Cross-platform support
  • 103
    Great community
  • 77
  • 75
    Full-text indexing and searching
  • 25
    Fast, open, available
  • 14
    SSL support
  • 13
  • 13
  • 8
    Enterprise Version
  • 7
    Easy to set up on all platforms
  • 1
    Easy, light, scalable
  • 1
    Relational database
  • 1
    NoSQL access to JSON data type
  • 1
    Sequel Pro (best SQL GUI)
  • 1
    Replica Support

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Cons of MariaDB
Cons of MongoDB
Cons of MySQL
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    • 5
      Very slowly for connected models that require joins
    • 3
      Not acid compliant
    • 1
      Proprietary query language
    • 13
      Owned by a company with their own agenda
    • 1
      Can't roll back schema changes

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