DBMS > Graph Engine vs. H2 vs. Raima Database Manager vs. TimescaleDB

System Properties Comparison Graph Engine vs. H2 vs. Raima Database Manager vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

RDBMS with a small footprint, either embedded into an application or used as a database server

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

Primary database model

Graph DBMS
Key-value store

Relational DBMS

Relational DBMS
Time Series DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	0.48
Rank	#261	Overall
	#122	Relational DBMS
	#22	Time Series DBMS

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Website

Technical documentation

www.graphengine.io/docs/manual

www.h2database.com/html/main.html

docs.raima.com

docs.timescale.com

Developer

Microsoft

Thomas Mueller

Raima Inc.

Timescale

Initial release

2010

2005

1984

2017

Current release

2.2.220, July 2023

15, June 2021

2.13.0, November 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

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

commercial

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

.NET and C

Java

Server operating systems

.NET

All OS with a Java VM

Android
HP-UX
Integrity RTOS
iOS
Linux
OS X
QNX
Solaris
VxWorks
Windows

Linux
OS X
Windows

Data scheme

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.

Exporting/Importing of XML structures possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

full PostgreSQL SQL syntax

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC
RESTful HTTP API

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

Supported programming languages

C#
C++
F#
Visual Basic

Java

.Net
C
C++
Objective-C
PL/SQL

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

yes

based on the ANSI/ISO SQL Persistent Stored Modules (PSM) specification

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

horizontal partitioning

none

horizontal partitioning

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

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

Immediate Consistency or Eventual Consistency depending on configuration

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

More information provided by the system vendor

Specific characteristics

Raima Database Manager (RDM) is an embedded time-series database optimized to run...
» more

Competitive advantages

Decreased time-to-market Industry-standard interfaces & tools for making your job...
» more

Typical application scenarios

Typical use cases include: Internet of Things (IoT) Embedded In-Memory Database Time-Series...
» more

Key customers

Infor, ABB, The Boeing Company, BAE Systems, Dow Jones, Dun & Bradstreet, Fujitsu,...
» more

Market metrics

Over 30 000 applications developers worldwide have field-tested RDM products More...
» more

Licensing and pricing models

Just as the technical aspects of Raima Database Manager are flexible, so are the...
» more

News

Raima Unveils RaimaDB 16.0: Elevating Database Performance and User Experience
29 February 2024

Raima Announces Release of Raima Database Manager (RDM) v15, a Powerful Embedded Time Series Database
10 June 2021

Raima Announces Release of Raima Database Manager (RDM) v14.2, a Powerful IoT Edge Embedded Database
8 October 2020

Raima Joins BlackBerry QNX Channel Partner Program to Deliver Safety-Critical and Secure Software Solutions
1 October 2020

Raima Expands Their Reseller Network in Asia
19 May 2020

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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