DBMS > H2GIS vs. PostGIS vs. Splice Machine

System Properties Comparison H2GIS vs. PostGIS vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

Spatial extension of H2

Spatial extension of PostgreSQL

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

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	0.04
Rank	#367	Overall
	#7	Spatial DBMS

Score	19.96
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.54
Rank	#239	Overall
	#112	Relational DBMS

Website

www.h2gis.org

postgis.net

splicemachine.com

Technical documentation

www.h2gis.org/docs/home

postgis.net/documentation

splicemachine.com/how-it-works

Developer

CNRS

Splice Machine

Initial release

2013

2005

2014

Current release

3.4.2, February 2024

3.1, March 2021

License

Commercial or Open Source

Open Source

LGPL 3.0

Open Source

GPL v2.0

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Java

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

Server-side scripts

Stored procedures

yes

based on H2

user defined functions

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

based on PostgreSQL

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

yes

based on PostgreSQL

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

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, multi-version concurrency control (MVCC)

yes

yes, multi-version concurrency control (MVCC)

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

yes

based on H2

yes

based on PostgreSQL

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

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