DBMS > Amazon DynamoDB vs. IBM Db2 warehouse vs. KairosDB vs. Microsoft Azure Cosmos DB vs. MonetDB

System Properties Comparison Amazon DynamoDB vs. IBM Db2 warehouse vs. KairosDB vs. Microsoft Azure Cosmos DB vs. MonetDB

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Cloud-based data warehousing service

Distributed Time Series DBMS based on Cassandra or H2

Globally distributed, horizontally scalable, multi-model database service

A relational database management system that stores data in columns

Primary database model

Document store
Key-value store

Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

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

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Website

aws.amazon.com/dynamodb

www.ibm.com/products/db2/warehouse

github.com/kairosdb/kairosdb

azure.microsoft.com/services/cosmos-db

www.monetdb.org

Technical documentation

docs.aws.amazon.com/dynamodb

kairosdb.github.io

learn.microsoft.com/azure/cosmos-db

www.monetdb.org/Documentation

Developer

Amazon

IBM

Microsoft

MonetDB BV

Initial release

2012

2014

2013

2014

2004

Current release

1.2.2, November 2018

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache 2.0

commercial

Open Source

Mozilla Public License 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

Java

Server operating systems

hosted

Linux
OS X
Windows

hosted

FreeBSD
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.

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

yes

SQL 2003 with some extensions

APIs and other access methods

RESTful HTTP API

.NET Client API
JDBC
ODBC
OLE DB

Graphite protocol
HTTP REST
Telnet API

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

Java
JavaScript

Node.js
PHP
Python

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

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

Server-side scripts

Stored procedures

PL/SQL, SQL PL

JavaScript

yes, in SQL, C, R

Triggers

yes

by integration with AWS Lambda

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

yes

Implicit feature of the cloud service

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

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 for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

simple password-based access control

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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