PostgreSQL vs TokuMX

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PostgreSQL
PostgreSQL

19.1K
14.9K
+ 1
3.4K
TokuMX
TokuMX

6
8
+ 1
3
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PostgreSQL vs TokuMX: What are the differences?

PostgreSQL: A powerful, open source object-relational database system. 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; TokuMX: A high-performance, concurrent, compressing, drop-in replacement engine for MongoDB. TokuMX is a drop-in replacement for MongoDB, and offers 20X performance improvements, 90% reduction in database size, and support for ACID transactions with MVCC. TokuMX has the same binaries, supports the same drivers, data model, and features of MongoDB, because it shares much of its code with MongoDB.

PostgreSQL and TokuMX belong to "Databases" category of the tech stack.

"Relational database" is the primary reason why developers consider PostgreSQL over the competitors, whereas "When your two-week MongoDB love affair ends, try this" was stated as the key factor in picking TokuMX.

PostgreSQL and TokuMX are both open source tools. It seems that PostgreSQL with 5.44K GitHub stars and 1.8K forks on GitHub has more adoption than TokuMX with 679 GitHub stars and 90 GitHub forks.

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.

What is TokuMX?

TokuMX is a drop-in replacement for MongoDB, and offers 20X performance improvements, 90% reduction in database size, and support for ACID transactions with MVCC. TokuMX has the same binaries, supports the same drivers, data model, and features of MongoDB, because it shares much of its code with MongoDB.
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    What are some alternatives to PostgreSQL and TokuMX?
    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.
    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.
    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.
    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.
    SQLite
    SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.
    See all alternatives
    Decisions about PostgreSQL and TokuMX
    Anton Sidelnikov
    Anton Sidelnikov
    Backend Developer at Beamery · | 8 upvotes · 9.6K views
    PostgreSQL
    PostgreSQL
    MongoDB
    MongoDB

    In my opinion PostgreSQL is totally over MongoDB - not only works with structured data & SQL & strict types, but also has excellent support for unstructured data as separate data type (you can store arbitrary JSONs - and they may be also queryable, depending on one of format's you may choose). Both writes & reads are much faster, then in Mongo. So you can get best on Document NoSQL & SQL in single database..

    Formal downside of PostgreSQL is clustering scalability. There's not simple way to build distributed a cluster. However, two points:

    1) You will need much more time before you need to actually scale due to PG's efficiency. And if you follow database-per-service pattern, maybe you won't need ever, cause dealing few billion records on single machine is an option for PG.

    2) When you need to - you do it in a way you need, including as a part of app's logic (e.g. sharding by key, or PG-based clustering solution with strict model), scalability will be very transparent, much more obvious than Mongo's "cluster just works (but then fails)" replication.

    See more
    Yonas Beshawred
    Yonas Beshawred
    CEO at StackShare · | 9 upvotes · 34.6K views
    atStackShareStackShare
    MemCachier
    MemCachier
    PostgreSQL
    PostgreSQL
    Rails
    Rails
    Amazon ElastiCache
    Amazon ElastiCache
    Heroku
    Heroku
    Memcached
    Memcached
    #Caching
    #RailsCaching

    We decided to use MemCachier as our Memcached provider because we were seeing some serious PostgreSQL performance issues with query-heavy pages on the site. We use MemCachier for all Rails caching and pretty aggressively too for the logged out experience (fully cached pages for the most part). We really need to move to Amazon ElastiCache as soon as possible so we can stop paying so much. The only reason we're not moving is because there are some restrictions on the network side due to our main app being hosted on Heroku.

    #Caching #RailsCaching

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    John Kodumal
    John Kodumal
    CTO at LaunchDarkly · | 15 upvotes · 268.2K views
    atLaunchDarklyLaunchDarkly
    Amazon RDS
    Amazon RDS
    PostgreSQL
    PostgreSQL
    TimescaleDB
    TimescaleDB
    Patroni
    Patroni
    Consul
    Consul
    Amazon ElastiCache
    Amazon ElastiCache
    Amazon EC2
    Amazon EC2
    Redis
    Redis
    Amazon Kinesis
    Amazon Kinesis
    Kafka
    Kafka

    As we've evolved or added additional infrastructure to our stack, we've biased towards managed services. Most new backing stores are Amazon RDS instances now. We do use self-managed PostgreSQL with TimescaleDB for time-series data—this is made HA with the use of Patroni and Consul.

    We also use managed Amazon ElastiCache instances instead of spinning up Amazon EC2 instances to run Redis workloads, as well as shifting to Amazon Kinesis instead of Kafka.

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    Joshua Dean Küpper
    Joshua Dean Küpper
    CEO at Scrayos UG (haftungsbeschränkt) · | 5 upvotes · 84.3K views
    atScrayos UG (haftungsbeschränkt)Scrayos UG (haftungsbeschränkt)
    MariaDB
    MariaDB
    PostgreSQL
    PostgreSQL
    GitLab
    GitLab
    Sentry
    Sentry

    We primarily use MariaDB but use PostgreSQL as a part of GitLab , Sentry and @Nextcloud , which (initially) forced us to use it anyways. While this isn't much of a decision – because we didn't have one (ha ha) – we learned to love the perks and advantages of PostgreSQL anyways. PostgreSQLs extension system makes it even more flexible than a lot of the other SQL-based DBs (that only offer stored procedures) and the additional JOIN options, the enhanced role management and the different authentication options came in really handy, when doing manual maintenance on the databases.

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    Alex A
    Alex A
    Founder at PRIZ Guru · | 6 upvotes · 8.6K views
    atPRIZ GuruPRIZ Guru
    MySQL
    MySQL
    PostgreSQL
    PostgreSQL

    One of our battles at the very beginning of the road was choosing the right database. In fact, our first prototype was built on MySQL and back then nothing else was even under a consideration (don't ask me why). At some point, I was working on a project which was running on PostgreSQL and it is only then I understood the full power of it. We have over a billion of records in production instance, and we are able to optimize it to run fast and reliable. Well, now my default DB is PostgreSQL :)

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    Tim Nolet
    Tim Nolet
    Founder, Engineer & Dishwasher at Checkly · | 8 upvotes · 69K views
    atChecklyHQChecklyHQ
    PostgreSQL
    PostgreSQL
    Heroku
    Heroku
    Node.js
    Node.js
    MongoDB
    MongoDB
    Amazon DynamoDB
    Amazon DynamoDB

    PostgreSQL Heroku Node.js MongoDB Amazon DynamoDB

    When I started building Checkly, one of the first things on the agenda was how to actually structure our SaaS database model: think accounts, users, subscriptions etc. Weirdly, there is not a lot of information on this on the "blogopshere" (cringe...). After research and some false starts with MongoDB and Amazon DynamoDB we ended up with PostgreSQL and a schema consisting of just four tables that form the backbone of all generic "Saasy" stuff almost any B2B SaaS bumps into.

    In a nutshell:cPostgreSQL Heroku Node.js MongoDB Amazon DynamoDB

    When I started building Checkly, one of the first things on the agenda was how to actually structure our SaaS database model: think accounts, users, subscriptions etc. Weirdly, there is not a lot of information on this on the "blogopshere" (cringe...). After research and some false starts with MongoDB and Amazon DynamoDB we ended up with PostgreSQL and a schema consisting of just four tables that form the backbone of all generic "Saasy" stuff almost any B2B SaaS bumps into.

    In a nutshell:

    • We use Postgres on Heroku.
    • We use a "one database, on schema" approach for partitioning customer data.
    • We use an accounts, memberships and users table to create a many-to-many relation between users and accounts.
    • We completely decouple prices, payments and the exact ingredients for a customer's plan.

    All the details including a database schema diagram are in the linked blog post.

    See more
    Łukasz Korecki
    Łukasz Korecki
    CTO & Co-founder at EnjoyHQ · | 12 upvotes · 83.7K views
    atEnjoyHQEnjoyHQ