DBMS > Cubrid vs. Sphinx vs. STSdb vs. Warp 10

System Properties Comparison Cubrid vs. Sphinx vs. STSdb vs. Warp 10

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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

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

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

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	6.03
Rank	#60	Overall
	#6	Search engines

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Score	0.08
Rank	#358	Overall
	#35	Time Series DBMS

Website

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

sphinxsearch.com

github.com/STSSoft/STSdb4

www.warp10.io

Technical documentation

cubrid.org/manuals

sphinxsearch.com/docs

www.warp10.io/content/02_Getting_started

Developer

CUBRID Corporation, CUBRID Foundation

Sphinx Technologies Inc.

STS Soft SC

SenX

Initial release

2008

2001

2011

2015

Current release

11.0, January 2021

3.5.1, February 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GPL version 2, commercial licence available

Open Source

GPLv2, commercial license available

Open Source

Apache License 2.0

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

C++

Java

Server operating systems

Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Proprietary protocol

.NET Client API

HTTP API
Jupyter
WebSocket

Supported programming languages

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes

WarpScript

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

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources

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The DB-Engines ranking includes now search engines
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