DBMS > Faircom DB vs. Netezza vs. PouchDB vs. RocksDB vs. Sphinx

System Properties Comparison Faircom DB vs. Netezza vs. PouchDB vs. RocksDB vs. Sphinx

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.

Data warehouse and analytics appliance part of IBM PureSystems

JavaScript DBMS with an API inspired by CouchDB

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

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Key-value store
Relational DBMS

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

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

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

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

www.faircom.com/products/faircom-db

www.ibm.com/products/netezza

pouchdb.com

rocksdb.org

sphinxsearch.com

Technical documentation

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

pouchdb.com/guides

github.com/facebook/rocksdb/wiki

sphinxsearch.com/docs

Developer

FairCom Corporation

IBM

Apache Software Foundation

Facebook, Inc.

Sphinx Technologies Inc.

Initial release

1979

2000

2012

2013

2001

Current release

V12, November 2020

7.1.1, June 2019

8.11.4, April 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

BSD

Open Source

GPL version 2, commercial licence available

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++

JavaScript

C++

Server operating systems

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

easily portable to other OSs

Linux

included in appliance

server-less, requires a JavaScript environment (browser, Node.js)

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

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

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

via views

yes

full-text index on all search fields

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

yes

SQL-like query language (SphinxQL)

APIs and other access methods

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

JDBC
ODBC
OLE DB

HTTP REST

only for PouchDB Server
JavaScript API

C++ API
Java API

Proprietary protocol

Supported programming languages

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

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

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).

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

Eventual Consistency

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

yes

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

by using IndexedDB, WebSQL or LevelDB as backend

yes

The original contents of fields are not stored in the Sphinx index.

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

Users with fine-grained authorization concept

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