DBMS > Citus vs. H2 vs. Percona Server for MongoDB vs. Quasardb vs. RocksDB

System Properties Comparison Citus vs. H2 vs. Percona Server for MongoDB vs. Quasardb vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Distributed, high-performance timeseries database

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Secondary database models

Document store

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

www.citusdata.com

www.h2database.com

www.percona.com/mongodb/software/percona-server-for-mongodb

quasar.ai

rocksdb.org

Technical documentation

docs.citusdata.com

www.h2database.com/html/main.html

docs.percona.com/percona-distribution-for-mongodb

doc.quasar.ai/master

github.com/facebook/rocksdb/wiki

Developer

Thomas Mueller

Percona

quasardb

Facebook, Inc.

Initial release

2010

2005

2015

2009

2013

Current release

8.1, December 2018

2.2.220, July 2023

3.4.10-2.10, November 2017

3.14.1, January 2024

8.11.4, April 2024

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

GPL Version 2

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

Linux

All OS with a Java VM

Linux

BSD
Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

with tags

SQL

Support of SQL

yes

standard, with numerous extensions

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC

proprietary protocol using JSON

HTTP API

C++ API
Java API

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Java Stored Procedures and User-Defined Functions

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

consistent hashing

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

With clustering: 2 database servers on different computers operate on identical copies of a database

Source-replica replication

Source-replica replication with selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

via In-Memory Engine

yes

Transient mode

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

Cryptographically strong user authentication and audit trail

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