DBMS > Altibase vs. Atos Standard Common Repository vs. SAP HANA vs. Splice Machine

System Properties Comparison Altibase vs. Atos Standard Common Repository vs. SAP HANA vs. Splice Machine

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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.

Description

An enterprise grade, high-performance RDBMS

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

In-memory, column based data store. Available as appliance or cloud service

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

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

altibase.com

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

www.sap.com/products/hana.html

splicemachine.com

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

help.sap.com/hana

splicemachine.com/how-it-works

Developer

Altibase

Atos Convergence Creators

SAP

Splice Machine

Initial release

1999

2016

2010

2014

Current release

v7.3, 2023, August 2023

1703

2.0 SPS07 (April 4, 2023), April 2023

3.1, March 2021

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

Server operating systems

AIX
HP-UX
Linux

Linux

Appliance or cloud-service

Linux
OS X
Solaris
Windows

Data scheme

yes

Schema and schema-less with LDAP views

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

SQL

Support of SQL

ANSI SQL-92

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

LDAP

JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C
C++
Java

All languages with LDAP bindings

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

Server-side scripts

Stored procedures

stored procedures and stored functions

SQLScript, R

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

LDAP bind authentication

yes

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

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