DBMS > Cubrid vs. Datomic vs. OpenQM vs. Warp 10

System Properties Comparison Cubrid vs. Datomic vs. OpenQM 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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

QpenQM is a high-performance, self-tuning, multi-value DBMS

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

Primary database model

Relational DBMS

Multivalue DBMS

Time Series DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

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

www.datomic.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.warp10.io

Technical documentation

cubrid.org/manuals

docs.datomic.com

www.warp10.io/content/02_Getting_started

Developer

CUBRID Corporation, CUBRID Foundation

Cognitect

Rocket Software, originally Martin Phillips

SenX

Initial release

2008

2012

1993

2015

Current release

11.0, January 2021

1.0.6735, June 2023

3.4-12

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

limited edition free

Open Source

GPLv2, extended 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

Java, Clojure

Java

Server operating systems

Linux
Windows

All OS with a Java VM

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

with some exceptions

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

HTTP API
Jupyter
WebSocket

Supported programming languages

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

Clojure
Java

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Transaction Functions

yes

WarpScript

Triggers

yes

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

yes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

But extensive use of caching in the application peers

yes

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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