DBMS > Amazon DocumentDB vs. Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. MonetDB vs. Yanza

System Properties Comparison Amazon DocumentDB vs. Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. MonetDB vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

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

Globally distributed, horizontally scalable, multi-model database service

A relational database management system that stores data in columns

Time Series DBMS for IoT Applications

Primary database model

Document store

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Secondary database models

Vector DBMS

Spatial DBMS

Document store
Spatial DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	5.59
Rank	#63	Overall
	#7	Search engines

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/documentdb

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

azure.microsoft.com/services/cosmos-db

www.monetdb.org

yanza.com

Technical documentation

aws.amazon.com/documentdb/resources

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

learn.microsoft.com/azure/cosmos-db

www.monetdb.org/Documentation

Developer

Microsoft

MonetDB BV

Yanza

Initial release

2019

2015

2014

2004

2015

Current release

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Windows

Data scheme

schema-free

yes

schema-free

yes

schema-free

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

SQL 2003 with some extensions

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

RESTful HTTP API

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C#
Java
JavaScript
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

any language that supports HTTP calls

Server-side scripts

Stored procedures

JavaScript

yes, in SQL, C, R

Triggers

JavaScript

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Sharding via remote tables

none

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

yes

Implicit feature of the cloud service

none

Source-replica replication available in experimental status

none

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

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

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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