DBMS > Microsoft Azure Table Storage vs. PouchDB vs. Sadas Engine vs. SAP SQL Anywhere vs. Snowflake

System Properties Comparison Microsoft Azure Table Storage vs. PouchDB vs. Sadas Engine vs. SAP SQL Anywhere vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

JavaScript DBMS with an API inspired by CouchDB

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Wide column store

Document store

Relational DBMS

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

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

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

pouchdb.com

www.sadasengine.com

www.sap.com/products/technology-platform/sql-anywhere.html

www.snowflake.com

Technical documentation

pouchdb.com/guides

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

help.sap.com/docs/SAP_SQL_Anywhere

docs.snowflake.net/manuals/index.html

Developer

Microsoft

Apache Software Foundation

SADAS s.r.l.

SAP

formerly Sybase

Snowflake Computing Inc.

Initial release

2012

2006

1992

2014

Current release

7.1.1, June 2019

8.0

17, July 2015

License

Commercial or Open Source

commercial

Open Source

commercial

free trial version available

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

JavaScript

C++

Server operating systems

hosted

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

AIX
Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

JDBC
ODBC
Proprietary protocol

ADO.NET
HTTP API
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

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

JavaScript

.Net
C
C#
C++
Groovy
Java
PHP
Python

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

View functions in JavaScript

yes, in C/C++, Java, .Net or Perl

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Source-replica replication

Database mirroring

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

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

managed by 'Learn by Usage'

yes

User concepts

Access control

Access rights based on private key authentication or shared access signatures

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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