DBMS > Microsoft Azure Cosmos DB vs. Oracle NoSQL vs. SAP SQL Anywhere vs. WakandaDB

System Properties Comparison Microsoft Azure Cosmos DB vs. Oracle NoSQL vs. SAP SQL Anywhere vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Document store
Key-value store
Relational DBMS

Relational DBMS

Object oriented DBMS

Secondary database models

Spatial DBMS

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

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

azure.microsoft.com/services/cosmos-db

www.oracle.com/database/nosql/technologies/nosql

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

wakanda.github.io

Technical documentation

learn.microsoft.com/azure/cosmos-db

docs.oracle.com/en/database/other-databases/nosql-database/index.html

help.sap.com/docs/SAP_SQL_Anywhere

wakanda.github.io/doc

Developer

Microsoft

Oracle

SAP

formerly Sybase

Wakanda SAS

Initial release

2014

2011

1992

2012

Current release

23.3, December 2023

17, July 2015

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

Open Source

AGPLv3, extended commercial license available

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

hosted

Linux
Solaris SPARC/x86

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

yes

APIs and other access methods

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

RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

RESTful HTTP API

Supported programming languages

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

C
C#
Go
Java
JavaScript (Node.js)
Python

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

JavaScript

Server-side scripts

Stored procedures

JavaScript

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

yes

Triggers

JavaScript

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

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication

Database mirroring

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

with Hadoop integration

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

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

configurable

ACID within a storage node (=shard)

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

off heap cache

yes

User concepts

Access control

Access rights can be defined down to the item level

Access rights for users and roles

fine grained access rights according to SQL-standard

yes

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