DBMS > Greenplum vs. H2GIS vs. Hazelcast vs. MySQL vs. PouchDB

System Properties Comparison Greenplum vs. H2GIS vs. Hazelcast vs. MySQL vs. PouchDB

Editorial information provided by DB-Engines

Name

Description

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Spatial extension of H2

A widely adopted in-memory data grid

Widely used open source RDBMS

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Key/Value like access via memcached API

Document store

Secondary database models

Document store
Spatial DBMS

Relational DBMS

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

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

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

Technical documentation

docs.greenplum.org

www.h2gis.org/docs/home

hazelcast.org/imdg/docs

dev.mysql.com/doc

pouchdb.com/guides

Developer

Pivotal Software Inc.

CNRS

Hazelcast

Oracle

since 2010, originally MySQL AB, then Sun

Apache Software Foundation

Initial release

2005

2013

2008

1995

2012

Current release

7.0.0, September 2023

5.3.6, November 2023

8.4.0, April 2024

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

LGPL 3.0

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

JavaScript

Server operating systems

Linux

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

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

Data scheme

yes

schema-free

yes

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

since Version 4.2

yes

the object must implement a serialization strategy

yes

Secondary indexes

yes

via views

SQL

Support of SQL

yes

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

C
Java
Perl
Python
R

Java

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript

Server-side scripts

Stored procedures

yes

based on H2

yes

Event Listeners, Executor Services

yes

proprietary syntax

View functions in JavaScript

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

based on H2

yes

Replicated Map

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

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

User concepts

Access control

fine grained access rights according to SQL-standard

yes

based on H2

Role-based access control

Users with fine-grained authorization concept

no user groups or roles

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