DBMS > Fujitsu Enterprise Postgres vs. GigaSpaces vs. H2 vs. SAP HANA vs. TimesTen

System Properties Comparison Fujitsu Enterprise Postgres vs. GigaSpaces vs. H2 vs. SAP HANA vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

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

In-memory, column based data store. Available as appliance or cloud service

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Graph DBMS
Search engine

Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.postgresql.fastware.com

www.gigaspaces.com

www.h2database.com

www.sap.com/products/hana.html

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

www.postgresql.fastware.com/product-manuals

docs.gigaspaces.com/latest/landing.html

www.h2database.com/html/main.html

help.sap.com/hana

docs.oracle.com/database/timesten-18.1

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Gigaspaces Technologies

Thomas Mueller

SAP

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2000

2005

2010

1998

Current release

Fujitsu Enterprise Postgres 14, January 2022

15.5, September 2020

2.2.220, July 2023

2.0 SPS07 (April 4, 2023), April 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

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

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, C++, .Net

Java

Server operating systems

Linux
Windows

Linux
macOS
Solaris
Windows

All OS with a Java VM

Appliance or cloud-service

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-99 for query and DML statements

yes

APIs and other access methods

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

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C++
Java
Python
Scala

Java

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

yes

Java Stored Procedures and User-Defined Functions

SQLScript, R

PL/SQL

Triggers

yes

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

Sharding

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

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

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

Role-based access control

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
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Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
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Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
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Licensing and pricing models

Core based licensing
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