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

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

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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

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

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Document store
Key-value store

Time Series DBMS

Relational DBMS

Document store

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	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

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

github.com/spotify/heroic

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

pouchdb.com

Technical documentation

spotify.github.io/heroic

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

pouchdb.com/guides

Developer

Atos Convergence Creators

Spotify

Microsoft

Apache Software Foundation

Initial release

2016

2014

2010

2012

Current release

1703

V12

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

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++

JavaScript

Server operating systems

Linux

hosted

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

schema-free

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

via Elasticsearch

yes

via views

SQL

Support of SQL

yes

APIs and other access methods

LDAP

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

ADO.NET
JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

All languages with LDAP bindings

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

JavaScript

Server-side scripts

Stored procedures

Transact SQL

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, with always 3 replicas available

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual 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

by using IndexedDB, WebSQL or LevelDB as backend

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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