DBMS > H2 vs. KairosDB vs. SAP Adaptive Server vs. TimescaleDB vs. Transbase

System Properties Comparison H2 vs. KairosDB vs. SAP Adaptive Server vs. TimescaleDB vs. Transbase

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.

Distributed Time Series DBMS based on Cassandra or H2

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

Relational DBMS

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

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	0.71
Rank	#230	Overall
	#20	Time Series DBMS

Score	37.12
Rank	#25	Overall
	#17	Relational DBMS

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Score	0.15
Rank	#337	Overall
	#147	Relational DBMS

Website

www.h2database.com

github.com/kairosdb/kairosdb

www.sap.com/products/technology-platform/sybase-ase.html

www.timescale.com

www.transaction.de/en/products/transbase.html

Technical documentation

www.h2database.com/html/main.html

kairosdb.github.io

help.sap.com/docs/SAP_ASE

docs.timescale.com

www.transaction.de/en/products/transbase/features.html

Developer

Thomas Mueller

SAP, Sybase

Timescale

Transaction Software GmbH

Initial release

2005

2013

1987

2017

1987

Current release

2.2.220, July 2023

1.2.2, November 2018

16.0

2.13.0, November 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

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

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

commercial

free development license

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++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

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

yes

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

yes

APIs and other access methods

JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

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

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java

Java
JavaScript

Node.js
PHP
Python

C
C++
Cobol
Java
Java
Perl
PHP
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Java and Transact-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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

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

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

Source-replica replication with hot standby and reads on replicas

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

yes

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

simple password-based access control

fine grained access rights according to SQL-standard

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More resources

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