DBMS > EsgynDB vs. Fujitsu Enterprise Postgres vs. Sadas Engine vs. TimesTen

System Properties Comparison EsgynDB vs. Fujitsu Enterprise Postgres vs. Sadas Engine vs. TimesTen

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.esgyn.cn

www.postgresql.fastware.com

www.sadasengine.com

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

Technical documentation

www.postgresql.fastware.com/product-manuals

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.oracle.com/database/timesten-18.1

Developer

Esgyn

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

SADAS s.r.l.

Oracle, TimesTen Performance Software, HP

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

Initial release

2015

2006

1998

Current release

Fujitsu Enterprise Postgres 14, January 2022

8.0

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free trial version available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Java

C++

Server operating systems

Linux

Linux
Windows

AIX
Linux
Windows

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

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

APIs and other access methods

ADO.NET
JDBC
ODBC

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

JDBC
ODBC
Proprietary protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

partitioning by range, list and by hash

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

none

Multi-source replication
Source-replica replication

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 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

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

managed by 'Learn by Usage'

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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...
» more

Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
» more

Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
» more

Licensing and pricing models

Core based licensing
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Fujitsu Develops Column-Oriented Data-Processing Engine Enabling Fast, High-Volume Data Analysis in Database ...
26 February 2015, Fujitsu

Supporting Business Continuity with Postgres on IBM Cloud LinuxONE Virtual Servers for VPC
24 September 2021, IBM

Primary Data says stop, Hammerspace, Innodisk cooks some SSDs, and Fujitsu goes blockchain
22 May 2018, The Register

provided by Google News

In-memory databases with Emulex Gen 7
25 October 2023, Broadcom Inc.

The Intel Xeon E7-8800 v3 Review: The POWER8 Killer?
8 May 2015, AnandTech

provided by Google News

Share this page