DBMS > Cubrid vs. EJDB vs. Sphinx vs. YottaDB

System Properties Comparison Cubrid vs. EJDB vs. Sphinx vs. YottaDB

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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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

A fast and solid embedded Key-value store

Primary database model

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

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

github.com/Softmotions/ejdb

sphinxsearch.com

yottadb.com

Technical documentation

cubrid.org/manuals

github.com/Softmotions/ejdb/blob/master/README.md

sphinxsearch.com/docs

yottadb.com/resources/documentation

Developer

CUBRID Corporation, CUBRID Foundation

Softmotions

Sphinx Technologies Inc.

YottaDB, LLC

Initial release

2008

2012

2001

Current release

11.0, January 2021

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GPLv2

Open Source

GPL version 2, commercial licence available

Open Source

AGPL 3.0

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++

Server operating systems

Linux
Windows

server-less

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Docker
Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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)

by using the Octo plugin

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

in-process shared library

Proprietary protocol

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

Java Stored Procedures

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

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

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

Users and groups based on OS-security mechanisms

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