DBMS > H2 vs. SiteWhere vs. SpatiaLite

System Properties Comparison H2 vs. SiteWhere vs. SpatiaLite

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Editorial information provided by DB-Engines

Name

Description

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

M2M integration platform for persisting/querying time series data

Spatial extension of SQLite

Primary database model

Relational DBMS

Time Series DBMS

Spatial DBMS

Secondary database models

Spatial DBMS

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
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Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	0.06
Rank	#367	Overall
	#36	Time Series DBMS

Score	1.72
Rank	#149	Overall
	#3	Spatial DBMS

Website

www.h2database.com

github.com/sitewhere/sitewhere

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

www.h2database.com/html/main.html

sitewhere1.sitewhere.io/index.html

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Thomas Mueller

SiteWhere

Alessandro Furieri

Initial release

2005

2010

2008

Current release

2.2.220, July 2023

5.0.0, August 2020

License

Commercial or Open Source

Open Source

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

Open Source

Common Public Attribution License Version 1.0

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

server-less

Data scheme

yes

predefined 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
ODBC

HTTP REST

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

none

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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