DBMS > Alibaba Cloud Table Store vs. Atos Standard Common Repository vs. EsgynDB vs. Riak KV vs. Sadas Engine

System Properties Comparison Alibaba Cloud Table Store vs. Atos Standard Common Repository vs. EsgynDB vs. Riak KV vs. Sadas Engine

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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

Distributed, fault tolerant key-value store

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

Primary database model

Wide column store

Document store
Key-value store

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

www.alibabacloud.com/product/table-store

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.esgyn.cn

www.sadasengine.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

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

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

Developer

Alibaba

Atos Convergence Creators

Esgyn

OpenSource, formerly Basho Technologies

SADAS s.r.l.

Initial release

2016

2015

2009

2006

Current release

1703

3.2.0, December 2022

8.0

License

Commercial or Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

commercial

free trial version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++, Java

Erlang

C++

Server operating systems

hosted

Linux

Linux
OS X

AIX
Linux
Windows

Data scheme

schema-free

Schema and schema-less with LDAP views

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

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

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP API

LDAP

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

JDBC
ODBC
Proprietary protocol

Supported programming languages

Java
Python

All languages with LDAP bindings

All languages supporting JDBC/ODBC/ADO.Net

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

Java Stored Procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

cell division

Sharding

no "single point of failure"

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Multi-source replication between multi datacenters

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

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

Transaction concepts

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

Atomic single-row operations

Atomic execution of specific operations

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

managed by 'Learn by Usage'

User concepts

Access control

Access rights based on subaccounts and tokens

LDAP bind authentication

fine grained access rights according to SQL-standard

yes, using Riak Security

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

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