DBMS > GeoMesa vs. H2 vs. Transwarp StellarDB

System Properties Comparison GeoMesa vs. H2 vs. Transwarp StellarDB

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Editorial information provided by DB-Engines

Name

Description

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Spatial DBMS

Relational DBMS

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Website

www.geomesa.org

www.h2database.com

www.transwarp.cn/en/product/stellardb

Technical documentation

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

www.h2database.com/html/main.html

Developer

CCRi and others

Thomas Mueller

Transwarp

Initial release

2014

2005

Current release

5.0.0, May 2024

2.2.220, July 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

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

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

Java

Server operating systems

All OS with a Java VM

Data scheme

yes

Typing

predefined data types such as float or date

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

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

OpenCypher

Supported programming languages

Java

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

With clustering: 2 database servers on different computers operate on identical copies of a database

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

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.

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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