Citus vs Vitess

Overview

Citus

Stacks60

Followers124

Votes11

GitHub Stars12.0K

Forks736

Vitess

Stacks66

Followers166

Votes0

Citus vs Vitess: What are the differences?

Architecture : Citus is an extension to Postgres that distributes data and queries across multiple nodes, allowing for horizontal scaling, while Vitess is a database clustering system for horizontal scaling of MySQL through sharding.
Supported Databases: Citus works with Postgres, enabling the use of Postgres' ecosystem and features, while Vitess is specifically designed for MySQL compatibility.
Query Language: Citus supports SQL queries with minimal changes needed, maintaining compatibility with existing tools, while Vitess requires the use of VTGate for routing queries, which means making changes to application connections and queries.
Consistency Model: Citus provides strong consistency within a Citus node but eventual consistency across nodes, while Vitess offers eventual consistency within a shard but strong consistency at the shard-level.
Data Sharding: Citus handles data distribution by distributing tables across nodes based on a distribution key, while Vitess automatically shards tables based on a predefined sharding key.
Use Cases: Citus is suitable for applications requiring complex queries or real-time analytics on large datasets, while Vitess is ideal for applications needing horizontal scalability for high read and write workloads on MySQL databases.

In Summary, Citus and Vitess have key differences in architecture, supported databases, query language, consistency model, data sharding, and ideal use cases.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Detailed Comparison

Citus	Vitess
It's an extension to Postgres that distributes data and queries in a cluster of multiple machines. Its query engine parallelizes incoming SQL queries across these servers to enable human real-time (less than a second) responses on large datasets.	It is a database solution for deploying, scaling and managing large clusters of MySQL instances. It’s architected to run as effectively in a public or private cloud architecture as it does on dedicated hardware. It combines and extends many important MySQL features with the scalability of a NoSQL database.
Multi-Node Scalable PostgreSQL;Built-in Replication and High Availability;Real-time Reads/Writes On Multiple Nodes;Multi-core Parallel Processing of Queries;Tenant isolation	Scalability; Connection pooling; Manageability
Statistics
GitHub Stars 12.0K	GitHub Stars -
GitHub Forks 736	GitHub Forks -
Stacks 60	Stacks 66
Followers 124	Followers 166
Votes 11	Votes 0
Pros & Cons
Pros 6 Multi-core Parallel Processing 3 Drop-in PostgreSQL replacement 2 Distributed with Auto-Sharding	No community feedback yet
Integrations
.NET Apache Spark Loggly Java Rails Datadog Logentries Heroku Papertrail PostgreSQL	Amazon RDS Kubernetes MySQL

What are some alternatives to Citus, Vitess?

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.

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.

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.

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

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.

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.

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

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.

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

Related Comparisons

Citus vs Vitess: What are the differences?

Architecture : Citus is an extension to Postgres that distributes data and queries across multiple nodes, allowing for horizontal scaling, while Vitess is a database clustering system for horizontal scaling of MySQL through sharding.
Supported Databases: Citus works with Postgres, enabling the use of Postgres' ecosystem and features, while Vitess is specifically designed for MySQL compatibility.
Query Language: Citus supports SQL queries with minimal changes needed, maintaining compatibility with existing tools, while Vitess requires the use of VTGate for routing queries, which means making changes to application connections and queries.
Consistency Model: Citus provides strong consistency within a Citus node but eventual consistency across nodes, while Vitess offers eventual consistency within a shard but strong consistency at the shard-level.
Data Sharding: Citus handles data distribution by distributing tables across nodes based on a distribution key, while Vitess automatically shards tables based on a predefined sharding key.
Use Cases: Citus is suitable for applications requiring complex queries or real-time analytics on large datasets, while Vitess is ideal for applications needing horizontal scalability for high read and write workloads on MySQL databases.

In Summary, Citus and Vitess have key differences in architecture, supported databases, query language, consistency model, data sharding, and ideal use cases.

Citus vs Vitess

Overview