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

Citus vs HSQLDB

OverviewComparisonAlternatives

Overview

Citus
Citus
Stacks60
Followers124
Votes11
GitHub Stars12.0K
Forks736
HSQLDB
HSQLDB
Stacks449
Followers61
Votes0
GitHub Stars86
Forks37

Citus vs HSQLDB: What are the differences?

Citus: Worry-free Postgres for SaaS. Built to scale out. Citus is worry-free Postgres for SaaS. Made to scale out, Citus is an extension to Postgres that distributes queries across any number of servers. Citus is available as open source, as on-prem software, and as a fully-managed service; HSQLDB: Leading SQL relational database software written in Java. It offers a small, fast multi-threaded and transactional database engine with in-memory and disk-based tables and supports embedded and server modes. It includes a powerful command line SQL tool and simple GUI query tools.

Citus and HSQLDB belong to "Databases" category of the tech stack.

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, HSQLDB provides the following key features:

  • Original code, based on in-depth study of database theory and the SQL Standard
  • Extensive syntax compatibility modes for porting from other database systems
  • The fastest overall open-source SQL implementation for small and medium sized databases

Citus and HSQLDB are both open source tools. It seems that Citus with 3.7K GitHub stars and 282 forks on GitHub has more adoption than HSQLDB with 11 GitHub stars and 5 GitHub forks.

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Detailed Comparison

Citus
Citus
HSQLDB
HSQLDB

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 offers a small, fast multi-threaded and transactional database engine with in-memory and disk-based tables and supports embedded and server modes. It includes a powerful command line SQL tool and simple GUI query tools.

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
Original code, based on in-depth study of database theory and the SQL Standard; Extensive syntax compatibility modes for porting from other database systems; The fastest overall open-source SQL implementation for small and medium sized databases; Three transaction control models, including lock based and MVCC models; Fully multi-threaded; Compact code footprint
Statistics
GitHub Stars
12.0K
GitHub Stars
86
GitHub Forks
736
GitHub Forks
37
Stacks
60
Stacks
449
Followers
124
Followers
61
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
.NET
Apache Spark
Apache Spark
Loggly
Loggly
Java
Java
Rails
Rails
Datadog
Datadog
Logentries
Logentries
Heroku
Heroku
Papertrail
Papertrail
PostgreSQL
PostgreSQL
Cloud 66
Cloud 66
Leftronic
Leftronic
Spring Boot
Spring Boot
Woopra
Woopra

What are some alternatives to Citus, HSQLDB?

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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