DBMS > Cachelot.io vs. Citus vs. Faircom DB vs. Percona Server for MongoDB vs. RocksDB

System Properties Comparison Cachelot.io vs. Citus vs. Faircom DB vs. Percona Server for MongoDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

In-memory caching system

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

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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

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

Primary database model

Key-value store

Relational DBMS

Key-value store
Relational DBMS

Document store

Key-value store

Secondary database models

Document store

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

Score	0.00
Rank	#396	Overall
	#64	Key-value stores

Score	2.15
Rank	#123	Overall
	#60	Relational DBMS

Score	0.24
Rank	#311	Overall
	#44	Key-value stores
	#140	Relational DBMS

Score	0.55
Rank	#253	Overall
	#39	Document stores

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

cachelot.io

www.citusdata.com

www.faircom.com/products/faircom-db

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

rocksdb.org

Technical documentation

docs.citusdata.com

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

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

github.com/facebook/rocksdb/wiki

Developer

FairCom Corporation

Percona

Facebook, Inc.

Initial release

2015

2010

1979

2015

2013

Current release

8.1, December 2018

V12, November 2020

3.4.10-2.10, November 2017

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

AGPL, commercial license also available

commercial

Restricted, free version available

Open Source

GPL Version 2

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

C++

ANSI C, C++

C++

Server operating systems

FreeBSD
Linux
OS X

Linux

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux

Data scheme

schema-free

yes

schema free, schema optional, schema required, partial schema,

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

yes

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

SQL

Support of SQL

yes

standard, with numerous extensions

yes, ANSI SQL with proprietary extensions

APIs and other access methods

Memcached protocol

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

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

proprietary protocol using JSON

C++ API
Java API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

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

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

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

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.

yes

.Net, JavaScript, C/C++

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

other methods possible by using 3rd party extensions

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

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

User concepts

Access control

fine grained access rights according to SQL-standard

Fine grained access rights according to SQL-standard with additional protections for files

Access rights for users and roles

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