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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Citus vs QuestDB

Citus vs QuestDB

OverviewComparisonAlternatives

Overview

Citus
Citus
Stacks60
Followers124
Votes11
GitHub Stars12.0K
Forks736
QuestDB
QuestDB
Stacks19
Followers50
Votes17
GitHub Stars16.3K
Forks1.5K

Citus vs QuestDB: What are the differences?

What is Citus? Worry-free Postgres for SaaS. 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.

What is QuestDB? Open source database for time series, events, and analytical workloads. It is an open source database for time series, events, and analytical workloads with a primary focus on performance. It enhances ANSI SQL with time series extensions to manipulate time stamped data.

Citus and QuestDB can be primarily classified as "Databases" tools.

Some of the features offered by Citus are:

  • Multi-Node Scalable PostgreSQL
  • Built-in Replication and High Availability
  • Real-time Reads/Writes On Multiple Nodes

On the other hand, QuestDB provides the following key features:

  • SIMD optimised analytics
  • Rows and columns based access
  • Vectorized queries execution

Citus is an open source tool with 4.25K GitHub stars and 337 GitHub forks. Here's a link to Citus's open source repository on GitHub.

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Detailed Comparison

Citus
Citus
QuestDB
QuestDB

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.

QuestDB is an open source database for time series, events, and analytical workloads with a primary focus on performance. It enhances ANSI SQL with time series extensions.

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
Relational model for time series; SIMD accelerated queries; Time partitioned; Heavy parallelization; Scalable ingestion; Immediate consistency; Time series and relational joins; Native InfluxDB line protocol; Grafana through Postgres wire support; Schema or schema-free; Aggregations and down sampling
Statistics
GitHub Stars
12.0K
GitHub Stars
16.3K
GitHub Forks
736
GitHub Forks
1.5K
Stacks
60
Stacks
19
Followers
124
Followers
50
Votes
11
Votes
17
Pros & Cons
Pros
  • 6
    Multi-core Parallel Processing
  • 3
    Drop-in PostgreSQL replacement
  • 2
    Distributed with Auto-Sharding
Pros
  • 2
    No dependencies
  • 2
    Real-time analytics
  • 2
    SQL
  • 2
    Postgres wire protocol
  • 2
    Open source
Integrations
.NET
.NET
Apache Spark
Apache Spark
Loggly
Loggly
Java
Java
Rails
Rails
Datadog
Datadog
Logentries
Logentries
Heroku
Heroku
Papertrail
Papertrail
PostgreSQL
PostgreSQL
InfluxDB
InfluxDB
Java
Java
PostgreSQL
PostgreSQL

What are some alternatives to Citus, QuestDB?

MongoDB

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

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

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

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

SQLite

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

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

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

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

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

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.

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