DBMS > Citus vs. DataFS vs. EDB Postgres vs. Hawkular Metrics vs. Tibero

System Properties Comparison Citus vs. DataFS vs. EDB Postgres vs. Hawkular Metrics vs. Tibero

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Secondary database models

Document store

Graph DBMS

Document store
Spatial DBMS

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	1.90
Rank	#135	Overall
	#63	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

us.tmaxsoft.com/products/tibero

Technical documentation

docs.citusdata.com

dev.mobiland.com/Overview.xsp

www.enterprisedb.com/docs

www.hawkular.org/hawkular-metrics/docs/user-guide

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Mobiland AG

EnterpriseDB

Community supported by Red Hat

TmaxSoft

Initial release

2010

2018

2005

2014

2003

Current release

8.1, December 2018

1.1.263, October 2022

14, December 2021

6, April 2015

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

commercial

BSD for PostgreSQL-components

Open Source

Apache 2.0

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

Java

C and Assembler

Server operating systems

Linux

Windows

Linux
Windows

Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

specific XML type available, but no XML query functionality

yes

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

yes

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

standard with numerous extensions

yes

APIs and other access methods

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

.NET Client API
Proprietary client DLL
WinRT client

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

HTTP REST

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

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

.Net
C
C#
C++
VB.Net

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

Go
Java
Python
Ruby

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

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

user defined functions

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

Persistent Stored Procedure (PSM)

Triggers

yes

no, except callback-events from server when changes happened

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Proprietary Sharding system

horizontal partitioning

by hash, list or range

Sharding

based on Cassandra

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

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

In-memory capabilities

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

planned for next version

User concepts

Access control

fine grained access rights according to SQL-standard

Windows-Profile

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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