DBMS > Sphinx vs. TerminusDB vs. VoltDB

System Properties Comparison Sphinx vs. TerminusDB vs. VoltDB

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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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Search engine

Graph DBMS

Relational DBMS

Secondary database models

Document store
RDF store

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

Score	6.03
Rank	#60	Overall
	#6	Search engines

Score	0.22
Rank	#323	Overall
	#28	Graph DBMS

Score	1.46
Rank	#159	Overall
	#74	Relational DBMS

Website

sphinxsearch.com

terminusdb.com

www.voltdb.com

Technical documentation

sphinxsearch.com/docs

terminusdb.github.io/terminusdb/#

docs.voltdb.com

Developer

Sphinx Technologies Inc.

DataChemist Ltd.

VoltDB Inc.

Initial release

2001

2018

2010

Current release

3.5.1, February 2023

11.0.0, January 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

GPL version 2, commercial licence available

Open Source

GPL V3

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++

Prolog, Rust

Java, C++

Server operating systems

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux

Linux
OS X

for development

Data scheme

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

SQL-like query language (SphinxQL)

SQL-like query language (WOQL)

yes

only a subset of SQL 99

APIs and other access methods

Proprietary protocol

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

JavaScript
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Journaling Streams

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

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

yes

in-memory journaling

yes

Snapshots and command logging

User concepts

Access control

Role-based access control

Users and roles with access to stored procedures

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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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