DBMS > Atos Standard Common Repository vs. SAP IQ vs. Snowflake vs. Splunk vs. Vitess

System Properties Comparison Atos Standard Common Repository vs. SAP IQ vs. Snowflake vs. Splunk vs. Vitess

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be 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

Cloud-based data warehousing service for structured and semi-structured data

Analytics Platform for Big Data

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Document store
Key-value store

column-oriented

Secondary database models

Document store
Spatial DBMS

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

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

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

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

www.snowflake.com

www.splunk.com

vitess.io

Technical documentation

help.sap.com/docs/SAP_IQ

docs.snowflake.net/manuals/index.html

docs.splunk.com/Documentation/Splunk

vitess.io/docs

Developer

Atos Convergence Creators

SAP, formerly Sybase

Snowflake Computing Inc.

Splunk Inc.

The Linux Foundation, PlanetScale

Initial release

2016

1994

2014

2003

2013

Current release

1703

16.1 SPS04, April 2019

15.0.2, December 2022

License

Commercial or Open Source

commercial

Limited free edition and free developer edition available

Open Source

Apache Version 2.0, commercial licenses 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

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows

hosted

Linux
OS X
Solaris
Windows

Docker
Linux
macOS

Data scheme

Schema and schema-less with LDAP views

yes

support of semi-structured data formats (JSON, XML, Avro)

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

Splunk Search Processing Language for search commands

yes

with proprietary extensions

APIs and other access methods

LDAP

ADO.NET
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

HTTP REST

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

All languages with LDAP bindings

C
C#
C++
Java
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

C#
Java
JavaScript
PHP
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

yes

proprietary syntax

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

shared disk or shared nothing architectures with SAP IQ Multiplexer

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

SAP/Sybase Replication Server

yes

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic execution of specific operations

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

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