Database Sharding vs Partitioning: What’s the Difference?

1. PostgreSQL

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   Mirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitting_a_Patch

   

   PostgreSQL and Partitioning PostgreSQL versions 10 and after have advanced native partitioning, making it ideal for time-series data, logs, and historical datasets. For example, a fintech app partitioning by month to improve query speeds.

2. Stream

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   Stream - Scalable APIs for Chat, Feeds, Moderation, & Video. Stream helps developers build engaging apps that scale to millions with performant and flexible Chat, Feeds, Moderation, and Video APIs and SDKs powered by a global edge network and enterprise-grade infrastructure.

   

3. MySQL

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   MySQL Server, the world's most popular open source database, and MySQL Cluster, a real-time, open source transactional database.

   

   MySQL MySQL natively supports partitioning, but sharding needs add-ons like Vitess to run platforms like YouTube.

4. MongoDB

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   The MongoDB Database

   

   It is helpful to consider how major platforms choose between database sharding vs partitioning, as this offers practical examples and advice. ** MongoDB and Sharding** MongoDB allows for the creation of shards with multiple copies. This is often used in apps like real-time analytics, gaming, large SaaS platforms, etc. For example, creating shards for a “users” collection by region to provide faster access and other local data benefits.

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