DBMS > DataFS vs. EDB Postgres vs. Riak TS vs. Sadas Engine

System Properties Comparison DataFS vs. EDB Postgres vs. Riak TS vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

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.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

Primary database model

Secondary database models

Graph DBMS

Document store
Spatial DBMS

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

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	1.86
Rank	#131	Overall
	#61	Relational DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

newdatabase.com

www.enterprisedb.com

www.sadasengine.com

Technical documentation

dev.mobiland.com/Overview.xsp

www.enterprisedb.com/docs

www.tiot.jp/riak-docs/riak/ts/latest

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

Developer

Mobiland AG

EnterpriseDB

Open Source, formerly Basho Technologies

SADAS s.r.l.

Initial release

2018

2005

2015

2006

Current release

1.1.263, October 2022

14, December 2021

3.0.0, September 2022

8.0

License

Commercial or Open Source

commercial

BSD for PostgreSQL-components

Open Source

commercial

free trial version available

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

Erlang

C++

Server operating systems

Windows

Linux
Windows

Linux
OS X

AIX
Linux
Windows

Data scheme

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.

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

standard with numerous extensions

yes, limited

yes

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

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

HTTP API
Native Erlang Interface

JDBC
ODBC
Proprietary protocol

Supported programming languages

.Net
C
C#
C++
VB.Net

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

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

Server-side scripts

Stored procedures

user defined functions

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

Erlang

Triggers

no, except callback-events from server when changes happened

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

horizontal partitioning

by hash, list or range

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

none

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

Foreign keys

Referential integrity

yes

links between datasets can be stored

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.

yes

managed by 'Learn by Usage'

User concepts

Access control

Windows-Profile

fine grained access rights according to SQL-standard

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

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