DBMS > Amazon CloudSearch vs. Amazon DocumentDB vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. Microsoft SQL Server

System Properties Comparison Amazon CloudSearch vs. Amazon DocumentDB vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

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

Database as a Service offering based on Apache CouchDB

Globally distributed, horizontally scalable, multi-model database service

Microsofts flagship relational DBMS

Primary database model

Search engine

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

aws.amazon.com/cloudsearch

aws.amazon.com/documentdb

www.ibm.com/products/cloudant

azure.microsoft.com/services/cosmos-db

www.microsoft.com/en-us/sql-server

Technical documentation

docs.aws.amazon.com/cloudsearch

aws.amazon.com/documentdb/resources

cloud.ibm.com/docs/Cloudant

learn.microsoft.com/azure/cosmos-db

learn.microsoft.com/en-US/sql/sql-server

Developer

Amazon

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

Initial release

2012

2019

2010

2014

1989

Current release

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Erlang

C++

Server operating systems

hosted

Linux
Windows

Data scheme

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.

yes

Secondary indexes

yes

all search fields are automatically indexed

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

HTTP API

proprietary protocol using JSON (MongoDB compatible)

RESTful HTTP/JSON API

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

JavaScript

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

none

Sharding

Implicit feature of the cloud service

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

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

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

atomic operations within a document possible

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

authentication via encrypted signatures

Access rights for users and roles

Access rights for users can be defined per database

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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