DBMS > Cubrid vs. InfinityDB vs. Sphinx vs. VoltDB

System Properties Comparison Cubrid vs. InfinityDB vs. Sphinx vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

A Java embedded Key-Value Store which extends the Java Map interface

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

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

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

cubrid.com (korean)
cubrid.org (english)

boilerbay.com

sphinxsearch.com

www.voltdb.com

Technical documentation

cubrid.org/manuals

boilerbay.com/infinitydb/manual

sphinxsearch.com/docs

docs.voltdb.com

Developer

CUBRID Corporation, CUBRID Foundation

Boiler Bay Inc.

Sphinx Technologies Inc.

VoltDB Inc.

Initial release

2008

2002

2001

2010

Current release

11.0, January 2021

4.0

3.5.1, February 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2, commercial licence available

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, C++, Java

Java

C++

Java, C++

Server operating systems

Linux
Windows

All OS with a Java VM

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X

for development

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Proprietary protocol

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

Java

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source 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

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

Snapshots and command logging

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

Users and roles with access to stored procedures

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More resources

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