DBMS > Amazon DocumentDB vs. Microsoft Azure Cosmos DB vs. SiteWhere vs. Transbase

System Properties Comparison Amazon DocumentDB vs. Microsoft Azure Cosmos DB vs. SiteWhere vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Globally distributed, horizontally scalable, multi-model database service

M2M integration platform for persisting/querying time series data

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.91
Rank	#124	Overall
	#22	Document stores

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.07
Rank	#347	Overall
	#33	Time Series DBMS

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Website

aws.amazon.com/documentdb

azure.microsoft.com/services/cosmos-db

github.com/sitewhere/sitewhere

www.transaction.de/en/products/transbase.html

Technical documentation

aws.amazon.com/documentdb/resources

learn.microsoft.com/azure/cosmos-db

sitewhere1.sitewhere.io/index.html

www.transaction.de/en/products/transbase/features.html

Developer

Microsoft

SiteWhere

Transaction Software GmbH

Initial release

2019

2014

2010

1987

Current release

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

commercial

free development license

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 and C++

Server operating systems

hosted

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

predefined scheme

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

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

HTTP REST

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

JavaScript

yes

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes

Implicit feature of the cloud service

selectable replication factor

based on HBase

Source-replica replication

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

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

Multi-item ACID transactions with snapshot isolation within a partition

yes

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 for users and roles

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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