DBMS > GBase vs. Geode vs. Hazelcast vs. PostgreSQL

System Properties Comparison GBase vs. Geode vs. Hazelcast vs. PostgreSQL

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Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

A widely adopted in-memory data grid

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

Relational DBMS

Key-value store

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Website

Technical documentation

geode.apache.org/docs

hazelcast.org/imdg/docs

www.postgresql.org/docs

Developer

General Data Technology Co., Ltd.

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Hazelcast

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2004

2002

2008

1989

1989: Postgres, 1996: PostgreSQL

Current release

GBase 8a, GBase 8s, GBase 8c

1.1, February 2017

5.3.6, November 2023

16.3, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache Version 2; commercial licenses available

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, Java, Python

Java

Server operating systems

Linux

All OS with a Java VM

the JDK (8 or later) is also required

All OS with a Java VM

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Data scheme

yes

schema-free

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.

yes

the object must implement a serialization strategy

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language (OQL)

SQL-like query language

yes

standard with numerous extensions

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

Java Client API
Memcached protocol
RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

yes

Event Listeners, Executor Services

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Cache Event Listeners

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

partitioning by range, list and (since PostgreSQL 11) by hash

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes

Replicated Map

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

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

ACID

Concurrency

Support for concurrent manipulation of data

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

yes

Access rights per client and object definable

Role-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

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