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

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

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Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

A high performance, scalable Wide Column DBMS

Platform for big data analytics on multistructured data sources and types

Primary database model

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	6.03
Rank	#60	Overall
	#6	Search engines

Score	0.01
Rank	#387	Overall
	#13	Wide column stores

Website

sphinxsearch.com

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

Technical documentation

sphinxsearch.com/docs

Developer

Sphinx Technologies Inc.

Alex Kashirin

Teradata

Initial release

2001

2020

2005

Current release

3.5.1, February 2023

0.5, April 2021

License

Commercial or Open Source

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++

Server operating systems

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language (SphinxQL)

SQL-like query language

yes

APIs and other access methods

Proprietary protocol

Proprietary protocol
Thrift

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C++

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

R packages

Triggers

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

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

Transaction concepts

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

ACID

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.

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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