DBMS > H2 vs. OushuDB vs. Prometheus vs. TimescaleDB

System Properties Comparison H2 vs. OushuDB vs. Prometheus vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

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

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Open-source Time Series DBMS and monitoring system

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

Spatial DBMS

Relational DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

www.h2database.com

www.oushu.com/product/oushuDB

prometheus.io

www.timescale.com

Technical documentation

www.h2database.com/html/main.html

www.oushu.com/documentation

prometheus.io/docs

docs.timescale.com

Developer

Thomas Mueller

Oushu

Timescale

Initial release

2005

2015

2017

Current release

2.2.220, July 2023

4.0.1, August 2020

2.15.0, May 2024

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

Apache 2.0

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

Java

Server operating systems

All OS with a Java VM

Linux

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Full-featured ANSI SQL support

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

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

Supported programming languages

Java

C
C++

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

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

yes

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

by Federation

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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, multi-version concurrency control (MVCC)

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

Kerberos, SSL and role based access

fine grained access rights according to SQL-standard

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