DBMS > Amazon DynamoDB vs. Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. SAP Adaptive Server

System Properties Comparison Amazon DynamoDB vs. Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. SAP Adaptive Server

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Editorial information provided by DB-Engines

Name

Description

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

Search-as-a-service for web and mobile app development

Globally distributed, horizontally scalable, multi-model database service

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Primary database model

Document store
Key-value store

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Vector DBMS

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	77.57
Rank	#16	Overall
	#2	Document stores
	#2	Key-value stores

Score	5.71
Rank	#64	Overall
	#8	Search engines

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	37.12
Rank	#25	Overall
	#17	Relational DBMS

Website

aws.amazon.com/dynamodb

azure.microsoft.com/en-us/services/search

azure.microsoft.com/services/cosmos-db

www.sap.com/products/technology-platform/sybase-ase.html

Technical documentation

docs.aws.amazon.com/dynamodb

learn.microsoft.com/en-us/azure/search

learn.microsoft.com/azure/cosmos-db

help.sap.com/docs/SAP_ASE

Developer

Amazon

Microsoft

SAP, Sybase

Initial release

2012

2015

2014

1987

Current release

16.0

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

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 and C++

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Unix
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.

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

RESTful HTTP 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

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
Java
JavaScript
Python

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

C
C++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

JavaScript

Java and Transact-SQL

Triggers

yes

by integration with AWS Lambda

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service

Multi-source replication
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

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

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

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.

User concepts

Access control

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

yes

using Azure authentication

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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