DBMS > JaguarDB vs. Sphinx vs. SWC-DB vs. Valentina Server

System Properties Comparison JaguarDB vs. Sphinx vs. SWC-DB vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Performant, highly scalable DBMS for AI and IoT applications

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

A high performance, scalable Wide Column DBMS

Object-relational database and reports server

Primary database model

Key-value store
Vector DBMS

Search engine

Wide column store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

www.jaguardb.com

sphinxsearch.com

github.com/kashirin-alex/swc-db
www.swcdb.org

www.valentina-db.net

Technical documentation

www.jaguardb.com/support.html

sphinxsearch.com/docs

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

DataJaguar, Inc.

Sphinx Technologies Inc.

Alex Kashirin

Paradigma Software

Initial release

2015

2001

2020

1999

Current release

3.3 July 2023

3.5.1, February 2023

0.5, April 2021

5.7.5

License

Commercial or Open Source

Open Source

GPL V3.0

Open Source

GPL version 2, commercial licence available

Open Source

GPL V3

commercial

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++

the server part. Clients available in other languages

C++

Server operating systems

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

full-text index on all search fields

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language (SphinxQL)

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

Proprietary protocol

Proprietary protocol
Thrift

ODBC

Supported programming languages

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C++

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

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

rights management via user accounts

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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