DBMS > IBM Db2 warehouse vs. Microsoft Azure Cosmos DB vs. RethinkDB vs. SwayDB vs. Tkrzw

System Properties Comparison IBM Db2 warehouse vs. Microsoft Azure Cosmos DB vs. RethinkDB vs. SwayDB vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

Cloud-based data warehousing service

Globally distributed, horizontally scalable, multi-model database service

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Key-value store

Secondary database models

Spatial DBMS

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

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

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

Score	2.66
Rank	#107	Overall
	#20	Document stores

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

www.ibm.com/products/db2/warehouse

azure.microsoft.com/services/cosmos-db

rethinkdb.com

swaydb.simer.au

dbmx.net/tkrzw

Technical documentation

learn.microsoft.com/azure/cosmos-db

rethinkdb.com/docs

Developer

IBM

Microsoft

The Linux Foundation

since July 2017

Simer Plaha

Mikio Hirabayashi

Initial release

2014

2009

2018

2020

Current release

2.4.1, August 2020

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

GNU Affero GPL V3.0

Open Source

Apache Version 2.0

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++

Scala

C++

Server operating systems

hosted

Linux
OS X
Windows

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

string, binary, float, bool, date, geometry

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.

Import/export of XML data possible

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

.NET Client API
JDBC
ODBC
OLE DB

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

Supported programming languages

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Java
Kotlin
Scala

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

PL/SQL, SQL PL

JavaScript

Triggers

yes

JavaScript

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

none

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

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Atomic single-document operations

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

yes

users and table-level permissions

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