DBMS > Microsoft Azure Table Storage vs. Postgres-XL vs. Sadas Engine vs. SAP SQL Anywhere

System Properties Comparison Microsoft Azure Table Storage vs. Postgres-XL vs. Sadas Engine vs. SAP SQL Anywhere

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Primary database model

Wide column store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

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

www.postgres-xl.org

www.sadasengine.com

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

Technical documentation

www.postgres-xl.org/documentation

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

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Microsoft

SADAS s.r.l.

SAP

formerly Sybase

Initial release

2012

2014

since 2012, originally named StormDB

2006

1992

Current release

10 R1, October 2018

8.0

17, July 2015

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

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

C++

Server operating systems

hosted

Linux
macOS

AIX
Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

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

XML type, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC
Proprietary protocol

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

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

Server-side scripts

Stored procedures

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

none

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.

none

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

optimistic locking

ACID

MVCC

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

managed by 'Learn by Usage'

yes

User concepts

Access control

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Working with Azure to Use and Manage Data Lakes
7 March 2024, Simplilearn

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, hackernoon.com

How to use Azure Table storage in .Net
14 January 2019, InfoWorld

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

Inside Azure File Storage
7 October 2015, azure.microsoft.com

provided by Google News

SAP vulnerabilities Let Attacker Inject OS Commands—Patch Now!
11 July 2023, CybersecurityNews

Securing SAP with AWS Network Firewall: Part 2 – Managed Rules | Amazon Web Services
17 July 2023, AWS Blog

MindsDB is now the leading and fastest growing applied ML platform in the world India - English
3 November 2022, PR Newswire

Gartner’s Magic Quadrant for Cloud Database Management Systems
9 December 2020, CRN

AWS, IBM, Microsoft, Google emerge Cloud DBMS leaders
22 December 2022, Daily Host News

provided by Google News

Share this page