DBMS > H2GIS vs. Heroic vs. Lovefield vs. Oracle vs. PouchDB

System Properties Comparison H2GIS vs. Heroic vs. Lovefield vs. Oracle vs. PouchDB

Editorial information provided by DB-Engines

Name

Description

Spatial extension of H2

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Embeddable relational database for web apps written in pure JavaScript

Widely used RDBMS

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Secondary database models

Relational DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

www.h2gis.org

github.com/spotify/heroic

google.github.io/lovefield

www.oracle.com/database

pouchdb.com

Technical documentation

www.h2gis.org/docs/home

spotify.github.io/heroic

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

docs.oracle.com/en/database

pouchdb.com/guides

Developer

CNRS

Spotify

Google

Oracle

Apache Software Foundation

Initial release

2013

2014

1980

2012

Current release

2.1.12, February 2017

23c, September 2023

7.1.1, June 2019

License

Commercial or Open Source

Open Source

LGPL 3.0

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

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

C and C++

JavaScript

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

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

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

schema-free

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

via Elasticsearch

yes

via views

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

with proprietary extensions

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

Java

JavaScript

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

JavaScript

Server-side scripts

Stored procedures

yes

based on H2

PL/SQL

also stored procedures in Java possible

View functions in JavaScript

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding, horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

yes

none

Multi-source replication
Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

isolation level can be parameterized

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

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

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

yes

using MemoryDB

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

yes

based on H2

fine grained access rights according to SQL-standard

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