DBMS > Cachelot.io vs. Citus vs. Faircom DB vs. H2

System Properties Comparison Cachelot.io vs. Citus vs. Faircom DB vs. H2

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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.

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

Primary database model

Key-value store

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store

Spatial DBMS

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

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Score	2.13
Rank	#117	Overall
	#56	Relational DBMS

Score	0.18
Rank	#314	Overall
	#45	Key-value stores
	#141	Relational DBMS

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Website

cachelot.io

www.citusdata.com

www.faircom.com/products/faircom-db

www.h2database.com

Technical documentation

docs.citusdata.com

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

www.h2database.com/html/main.html

Developer

FairCom Corporation

Thomas Mueller

Initial release

2015

2010

1979

2005

Current release

8.1, December 2018

V13, July 2024

2.2.220, July 2023

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

AGPL, commercial license also available

commercial

Restricted, free version available

Open Source

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

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++

Java

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

All OS with a Java VM

Data scheme

schema-free

yes

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

yes

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

yes

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

JDBC
ODBC

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

Java

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++

Java Stored Procedures and User-Defined Functions

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

none

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).

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

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

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

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Microsoft acquires Citus Data, re-affirming its commitment to Open Source and accelerating Azure PostgreSQL performance and scale
24 January 2019, Microsoft

Ubicloud wants to build an open source alternative to AWS
5 March 2024, TechCrunch

Microsoft acquires Citus Data, creators of a cloud-friendly version of the PostgreSQL database
24 January 2019, GeekWire

Microsoft buys an open source database startup to give it an edge against Amazon Web Services
24 January 2019, Business Insider

Microsoft acquires another open-source company, Citus Data
24 January 2019, CNBC

provided by Google News

FairCom Unveils New Look, FairCom DB v13: Introducing 'DB Made Simple'
4 June 2024, businesswire.com

provided by Google News

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