DBMS > H2 vs. IBM Db2 vs. Linter vs. OpenTSDB

System Properties Comparison H2 vs. IBM Db2 vs. Linter vs. OpenTSDB

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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.

Common in IBM host environments, 2 different versions for host and Windows/Linux

RDBMS for high security requirements

Scalable Time Series DBMS based on HBase

Primary database model

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Spatial DBMS

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

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	125.90
Rank	#9	Overall
	#6	Relational DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Website

www.h2database.com

www.ibm.com/products/db2

linter.ru

opentsdb.net

Technical documentation

www.h2database.com/html/main.html

www.ibm.com/docs/en/db2

opentsdb.net/docs/build/html/index.html

Developer

Thomas Mueller

IBM

relex.ru

currently maintained by Yahoo and other contributors

Initial release

2005

1983

host version

1990

2011

Current release

2.2.220, July 2023

12.1, October 2016

License

Commercial or Open Source

Open Source

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

commercial

free version is available

commercial

Open Source

LGPL

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

C and C++

Java

Server operating systems

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows
z/OS

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

HTTP API
Telnet API

Supported programming languages

Java

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

only with Windows/Unix/Linux Version

none

Sharding

based on HBase

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

with separate tools (MQ, InfoSphere)

Source-replica replication

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, 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

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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