DBMS > Sphinx vs. SWC-DB vs. Teradata vs. Transbase

System Properties Comparison Sphinx vs. SWC-DB vs. Teradata vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

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

A high performance, scalable Wide Column DBMS

A hybrid cloud data analytics software platform (Teradata Vantage)

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Search engine

Wide column store

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

sphinxsearch.com

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

www.teradata.com

www.transaction.de/en/products/transbase.html

Technical documentation

sphinxsearch.com/docs

docs.teradata.com

www.transaction.de/en/products/transbase/features.html

Developer

Sphinx Technologies Inc.

Alex Kashirin

Teradata

Transaction Software GmbH

Initial release

2001

2020

1984

1987

Current release

3.5.1, February 2023

0.5, April 2021

Teradata Vantage 1.0 MU2, January 2019

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

GPL version 2, commercial licence available

Open Source

GPL V3

commercial

free development 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++

C and C++

Server operating systems

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux

hosted
Linux

FreeBSD
Linux
macOS
Solaris
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.

yes

Secondary indexes

yes

full-text index on all search fields

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

yes

SQL

Support of SQL

SQL-like query language (SphinxQL)

SQL-like query language

yes

SQL 2016 + extensions

yes

APIs and other access methods

Proprietary protocol

Proprietary protocol
Thrift

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C++

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

UDFs, stored procedures, table functions in parallel

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

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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

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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Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

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