DBMS > Axibase vs. GeoMesa vs. SAP SQL Anywhere vs. Transwarp KunDB

System Properties Comparison Axibase vs. GeoMesa vs. SAP SQL Anywhere vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Time Series DBMS

Spatial DBMS

Relational DBMS

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	0.10
Rank	#344	Overall
	#151	Relational DBMS

Website

axibase.com/docs/atsd/finance

www.geomesa.org

www.sap.com/products/technology-platform/sql-anywhere.html

www.transwarp.cn/en/product/kundb

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Axibase Corporation

CCRi and others

SAP

formerly Sybase

Transwarp

Initial release

2013

2014

1992

Current release

15585

4.0.5, February 2024

17, July 2015

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache License 2.0

commercial

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

Scala

Server operating systems

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

SQL-like query language

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

yes, in C/C++, Java, .Net or Perl

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

depending on storage layer

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

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

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.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

yes

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More resources

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6 April 2021, Matthias Gelbmann

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