DBMS > Atos Standard Common Repository vs. SAP IQ vs. Splice Machine vs. Yaacomo

System Properties Comparison Atos Standard Common Repository vs. SAP IQ vs. Splice Machine vs. Yaacomo

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Editorial information provided by DB-Engines

Name

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

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

Columnar RDBMS optimized for Big Data analytics

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Key-value store

Relational DBMS

column-oriented

Relational DBMS

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

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

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

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

splicemachine.com

yaacomo.com

Technical documentation

help.sap.com/docs/SAP_IQ

splicemachine.com/how-it-works

Developer

Atos Convergence Creators

SAP, formerly Sybase

Splice Machine

Q2WEB GmbH

Initial release

2016

1994

2014

2009

Current release

1703

16.1 SPS04, April 2019

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

AGPL 3.0, commercial license 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

Java

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Solaris
Windows

Android
Linux
Windows

Data scheme

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes

APIs and other access methods

LDAP

ADO.NET
JDBC
ODBC
RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

C
C#
C++
Java
Perl
PHP
Python
Ruby

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

shared disk or shared nothing architectures with SAP IQ Multiplexer

Shared Nothhing Auto-Sharding, Columnar Partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

SAP/Sybase Replication Server

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

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

User concepts

Access control

LDAP bind authentication

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

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