DBMS > GeoMesa vs. H2GIS vs. Spark SQL vs. Splice Machine vs. Transbase

System Properties Comparison GeoMesa vs. H2GIS vs. Spark SQL vs. Splice Machine vs. Transbase

Editorial information provided by DB-Engines

Name

Description

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

Spatial extension of H2

Spark SQL is a component on top of 'Spark Core' for structured data processing

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

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

Primary database model

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

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

Technical documentation

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

www.h2gis.org/docs/home

spark.apache.org/docs/latest/sql-programming-guide.html

splicemachine.com/how-it-works

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

Developer

CCRi and others

CNRS

Apache Software Foundation

Splice Machine

Transaction Software GmbH

Initial release

2014

2013

2014

1987

Current release

5.0.0, May 2024

3.5.0 ( 2.13), September 2023

3.1, March 2021

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

LGPL 3.0

Open Source

Apache 2.0

Open Source

AGPL 3.0, commercial license available

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

Scala

Java

Scala

Java

C and C++

Server operating systems

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS
Solaris
Windows

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 DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java

Java
Python
R
Scala

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

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

Server-side scripts

Stored procedures

yes

based on H2

yes

Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

none

yes, utilizing Spark Core

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

based on H2

none

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

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

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

yes

based on H2

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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