DBMS > Cubrid vs. Derby vs. OpenMLDB vs. TimescaleDB

System Properties Comparison Cubrid vs. Derby vs. OpenMLDB vs. TimescaleDB

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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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

An open-source machine learning database that provides a feature platform for training and inference

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	0.10
Rank	#359	Overall
	#36	Time Series DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

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

db.apache.org/derby

openmldb.ai

www.timescale.com

Technical documentation

cubrid.org/manuals

db.apache.org/derby/manuals/index.html

openmldb.ai/docs/zh/main

docs.timescale.com

Developer

CUBRID Corporation, CUBRID Foundation

Apache Software Foundation

4 Paradigm Inc.

Timescale

Initial release

2008

1997

2020

2017

Current release

11.0, January 2021

10.17.1.0, November 2023

2024-2 February 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache version 2

Open Source

Apache 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

C++, Java, Scala

Server operating systems

Linux
Windows

All OS with a Java VM

Linux

Linux
OS X
Windows

Data scheme

yes

Fixed schema

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

full PostgreSQL SQL syntax

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JDBC

JDBC
SQLAlchemy

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

Java

C++
Go
Java
Python
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Source-replica replication with hot standby and reads on replicas

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

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

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

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