DBMS > CouchDB vs. Microsoft Azure Table Storage vs. PouchDB vs. SAP HANA vs. Teradata Aster

System Properties Comparison CouchDB vs. Microsoft Azure Table Storage vs. PouchDB vs. SAP HANA vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

A Wide Column Store for rapid development using massive semi-structured datasets

JavaScript DBMS with an API inspired by CouchDB

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

Platform for big data analytics on multistructured data sources and types

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

couchdb.apache.org

azure.microsoft.com/en-us/services/storage/tables

pouchdb.com

www.sap.com/products/hana.html

Technical documentation

docs.couchdb.org/en/stable

pouchdb.com/guides

help.sap.com/hana

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Microsoft

Apache Software Foundation

SAP

Teradata

Initial release

2005

2012

2010

2005

Current release

3.3.3, December 2023

7.1.1, June 2019

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

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

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Implementation language

Erlang

JavaScript

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

hosted

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

Appliance or cloud-service

Linux

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

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

in Aster File Store

Secondary indexes

yes

via views

yes

via views

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

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

JavaScript

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

View functions in JavaScript

SQLScript, R

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

Implicit feature of the cloud service

Sharding

with a proxy-based framework, named couchdb-lounge

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

Access rights for users can be defined per database

Access rights based on private key authentication or shared access signatures

yes

fine grained access rights according to SQL-standard

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