DBMS > EventStoreDB vs. H2GIS vs. Splice Machine

System Properties Comparison EventStoreDB vs. H2GIS vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Spatial extension of H2

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

Primary database model

Event Store

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	1.14
Rank	#181	Overall
	#1	Event Stores

Score	0.05
Rank	#372	Overall
	#7	Spatial DBMS

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Website

www.eventstore.com

www.h2gis.org

splicemachine.com

Technical documentation

developers.eventstore.com

www.h2gis.org/docs/home

splicemachine.com/how-it-works

Developer

Event Store Limited

CNRS

Splice Machine

Initial release

2012

2013

2014

Current release

21.2, February 2021

3.1, March 2021

License

Commercial or Open Source

Open Source

LGPL 3.0

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
Windows

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.

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

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

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)

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

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

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