DBMS > Microsoft Azure Cosmos DB vs. OpenTSDB vs. Riak KV vs. SiteWhere

System Properties Comparison Microsoft Azure Cosmos DB vs. OpenTSDB vs. Riak KV vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

Scalable Time Series DBMS based on HBase

Distributed, fault tolerant key-value store

M2M integration platform for persisting/querying time series data

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Time Series 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	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

azure.microsoft.com/services/cosmos-db

opentsdb.net

github.com/sitewhere/sitewhere

Technical documentation

learn.microsoft.com/azure/cosmos-db

opentsdb.net/docs/build/html/index.html

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

sitewhere1.sitewhere.io/index.html

Developer

Microsoft

currently maintained by Yahoo and other contributors

OpenSource, formerly Basho Technologies

SiteWhere

Initial release

2014

2011

2009

2010

Current release

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

LGPL

Open Source

Apache version 2, commercial enterprise edition

Open Source

Common Public Attribution License Version 1.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Erlang

Java

Server operating systems

hosted

Linux
Windows

Linux
OS X

Linux
OS X
Windows

Data scheme

schema-free

predefined scheme

Typing

predefined data types such as float or date

yes

JSON types

numeric data for metrics, strings for tags

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.

Secondary indexes

yes

All properties auto-indexed by default

restricted

SQL

Support of SQL

SQL-like query language

APIs and other access methods

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

HTTP API
Telnet API

HTTP API
Native Erlang Interface

HTTP REST

Supported programming languages

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

Erlang
Go
Java
Python
R
Ruby

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

Server-side scripts

Stored procedures

JavaScript

Erlang

Triggers

JavaScript

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

Sharding

no "single point of failure"

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

based on HBase

selectable replication factor

based on HBase

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

Immediate Consistency

based on HBase

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

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.

User concepts

Access control

Access rights can be defined down to the item level

yes, using Riak Security

Users with fine-grained authorization concept

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