DBMS > Apache Pinot vs. Atos Standard Common Repository vs. Microsoft Azure SQL Database vs. SAP HANA

System Properties Comparison Apache Pinot vs. Atos Standard Common Repository vs. Microsoft Azure SQL Database vs. SAP HANA

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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

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

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

Database as a Service offering with high compatibility to Microsoft SQL Server

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

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.35
Rank	#274	Overall
	#128	Relational DBMS

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Website

pinot.apache.org

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

azure.microsoft.com/en-us/products/azure-sql/database

www.sap.com/products/hana.html

Technical documentation

docs.pinot.apache.org

docs.microsoft.com/en-us/azure/azure-sql

help.sap.com/hana

Developer

Apache Software Foundation and contributors

Atos Convergence Creators

Microsoft

SAP

Initial release

2015

2016

2010

Current release

1.0.0, September 2023

1703

V12

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

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

Java

C++

Server operating systems

All OS with a Java JDK11 or higher

Linux

hosted

Appliance or cloud-service

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

SQL-like query language

yes

APIs and other access methods

JDBC

LDAP

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

Go
Java
Python

All languages with LDAP bindings

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

Transact SQL

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

cell division

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, with always 3 replicas available

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

yes

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