DBMS > Faircom DB vs. Memcached vs. SiriDB vs. STSdb vs. XTDB

System Properties Comparison Faircom DB vs. Memcached vs. SiriDB vs. STSdb vs. XTDB

Editorial information provided by DB-Engines

Name

Description

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

In-memory key-value store, originally intended for caching

Open Source Time Series DBMS

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store
Relational DBMS

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

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.faircom.com/products/faircom-db

www.memcached.org

siridb.com

github.com/STSSoft/STSdb4

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

github.com/memcached/memcached/wiki

docs.siridb.com

www.xtdb.com/docs

Developer

FairCom Corporation

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Cesbit

STS Soft SC

Juxt Ltd.

Initial release

1979

2003

2017

2011

2019

Current release

V12, November 2020

1.6.27, May 2024

4.0.8, September 2015

1.19, September 2021

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

BSD license

Open Source

MIT License

Open Source

GPLv2, commercial license available

Open Source

MIT 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

ANSI C, C++

Clojure

Server operating systems

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

easily portable to other OSs

FreeBSD
Linux
OS X
Unix
Windows

Linux

Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

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

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

Numeric data

yes

primitive types and user defined types (classes)

yes, extensible-data-notation format

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.

Secondary indexes

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

limited SQL, making use of Apache Calcite

APIs and other access methods

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

Proprietary protocol

HTTP API

.NET Client API

HTTP REST
JDBC

Supported programming languages

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

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

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

C#
Java

Clojure
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Repcached, a Memcached patch, provides this functionallity

yes

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 with additional protections for files

yes

using SASL (Simple Authentication and Security Layer) protocol

simple rights management via user accounts

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More resources

DB-Engines blog posts

Redis extends the lead in the DB-Engines key-value store ranking
3 February 2014, Matthias Gelbmann

New DB-Engines Ranking shows the popularity of database management systems
3 October 2012, Matthias Gelbmann, Paul Andlinger

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Recent citations in the news

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