DBMS > H2GIS vs. Lovefield vs. OushuDB

System Properties Comparison H2GIS vs. Lovefield vs. OushuDB

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Editorial information provided by DB-Engines

Name

Description

Spatial extension of H2

Embeddable relational database for web apps written in pure JavaScript

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

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Trend Chart

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Website

www.h2gis.org

google.github.io/lovefield

www.oushu.com/product/oushuDB

Technical documentation

www.h2gis.org/docs/home

github.com/google/lovefield/blob/master/docs/spec_index.md

www.oushu.com/documentation

Developer

CNRS

Google

Oushu

Initial release

2013

2014

Current release

2.1.12, February 2017

4.0.1, August 2020

License

Commercial or Open Source

Open Source

LGPL 3.0

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux

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

via JavaScript builder pattern

Full-featured ANSI SQL support

APIs and other access methods

JDBC
ODBC

Supported programming languages

Java

JavaScript

C
C++

Server-side scripts

Stored procedures

yes

based on H2

yes

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop 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

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

yes

based on H2

Kerberos, SSL and role based access

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