DBMS > H2 vs. Linter vs. OpenTSDB vs. TimescaleDB

System Properties Comparison H2 vs. Linter vs. OpenTSDB 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.

RDBMS for high security requirements

Scalable Time Series DBMS based on HBase

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	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	0.03
Rank	#368	Overall
	#156	Relational DBMS

Score	1.59
Rank	#140	Overall
	#12	Time Series DBMS

Score	4.06
Rank	#73	Overall
	#5	Time Series DBMS

Website

Technical documentation

www.h2database.com/html/main.html

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

docs.timescale.com

Developer

Thomas Mueller

relex.ru

currently maintained by Yahoo and other contributors

Timescale

Initial release

2005

1990

2011

2017

Current release

2.2.220, July 2023

2.15.0, May 2024

License

Commercial or Open Source

Open Source

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

commercial

Open Source

LGPL

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

C and C++

Java

Server operating systems

All OS with a Java VM

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

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

JDBC
ODBC

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

HTTP API
Telnet API

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

Supported programming languages

Java

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

Erlang
Go
Java
Python
R
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

proprietary syntax with the possibility to convert from PL/SQL

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

Sharding

based on HBase

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

selectable replication factor

based on HBase

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

based on HBase

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

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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

show all

Recent citations in the news

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

Brain Monitoring with Kafka, OpenTSDB, and Grafana
5 August 2016, KDnuggets

LogicMonitor Rolls a Time Series Database for Finer-Grain Reporting
1 June 2016, The New Stack

provided by Google News

General availability: Latest version of the TimeScaleDB extension on Azure Database for PostgreSQL - Flexible Server
8 May 2024, azure.microsoft.com

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions
11 June 2024, PR Newswire

Understanding Hyperfunctions in TimescaleDB
11 August 2021, CDOTrends

provided by Google News

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