DBMS > Atos Standard Common Repository vs. Heroic vs. Ingres vs. Microsoft Azure SQL Database

System Properties Comparison Atos Standard Common Repository vs. Heroic vs. Ingres vs. Microsoft Azure SQL Database

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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

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Well established RDBMS

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

Primary database model

Document store
Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Website

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

github.com/spotify/heroic

www.actian.com/databases/ingres

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

Technical documentation

spotify.github.io/heroic

docs.actian.com/ingres

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

Developer

Atos Convergence Creators

Spotify

Actian Corporation

Microsoft

Initial release

2016

2014

1974

originally developed at University Berkely in early 1970s

2010

Current release

1703

11.2, May 2022

V12

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

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++

Server operating systems

Linux

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

hosted

Data scheme

Schema and schema-less with LDAP views

schema-free

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

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

LDAP

HQL (Heroic Query Language, a JSON-based language)
HTTP API

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

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

Server-side scripts

Stored procedures

yes

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Ingres Replicator

yes, with always 3 replicas available

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

Eventual Consistency
Immediate Consistency

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

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

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