DBMS > Microsoft Azure Cosmos DB vs. Netezza vs. Riak TS vs. SAP SQL Anywhere

System Properties Comparison Microsoft Azure Cosmos DB vs. Netezza vs. Riak TS vs. SAP SQL Anywhere

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Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

Data warehouse and analytics appliance part of IBM PureSystems

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

azure.microsoft.com/services/cosmos-db

www.ibm.com/products/netezza

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

Technical documentation

learn.microsoft.com/azure/cosmos-db

www.tiot.jp/riak-docs/riak/ts/latest

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Microsoft

IBM

Open Source, formerly Basho Technologies

SAP

formerly Sybase

Initial release

2014

2000

2015

1992

Current release

3.0.0, September 2022

17, July 2015

License

Commercial or Open Source

commercial

Open Source

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

Erlang

Server operating systems

hosted

Linux

included in appliance

Linux
OS X

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

restricted

yes

SQL

Support of SQL

SQL-like query language

yes

yes, limited

yes

APIs and other access methods

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
ODBC
OLE DB

HTTP API
Native Erlang Interface

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

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

Server-side scripts

Stored procedures

JavaScript

yes

Erlang

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

Triggers

JavaScript

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

selectable replication factor

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

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

User concepts

Access control

Access rights can be defined down to the item level

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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