DBMS > Axibase vs. GeoMesa vs. Transwarp StellarDB

System Properties Comparison Axibase vs. GeoMesa vs. Transwarp StellarDB

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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.

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Time Series DBMS

Spatial DBMS

Graph DBMS

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

Score	0.22
Rank	#305	Overall
	#25	Time Series DBMS

Score	0.72
Rank	#220	Overall
	#4	Spatial DBMS

Score	0.00
Rank	#385	Overall
	#41	Graph DBMS

Website

axibase.com/docs/atsd/finance

www.geomesa.org

www.transwarp.cn/en/product/stellardb

Technical documentation

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

Developer

Axibase Corporation

CCRi and others

Transwarp

Initial release

2013

2014

Current release

15585

5.0.1, July 2024

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

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

OpenCypher

Supported programming languages

Go
Java
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

depending on storage layer

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

Foreign keys

Referential integrity

Transaction concepts

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

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

User concepts

Access control

yes

depending on the DBMS used for storage

yes

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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