DBMS > Amazon DocumentDB vs. Atos Standard Common Repository vs. Microsoft Azure Table Storage vs. searchxml

System Properties Comparison Amazon DocumentDB vs. Atos Standard Common Repository vs. Microsoft Azure Table Storage vs. searchxml

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Editorial information provided by DB-Engines
Name	Amazon DocumentDB  Xexclude from comparison	Atos Standard Common Repository  Xexclude from comparison	Microsoft Azure Table Storage  Xexclude from comparison	searchxml  Xexclude from comparison
		This system has been discontinued and will be removed from the DB-Engines ranking.
Description	Fast, scalable, highly available, and fully managed MongoDB-compatible database service	Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks	A Wide Column Store for rapid development using massive semi-structured datasets	DBMS for structured and unstructured content wrapped with an application server
Primary database model	Document store	Document store Key-value store	Wide column store	Native XML DBMS Search engine
DB-Engines Ranking measures the popularity of database management systems Trend Chart	Score 1.91 Rank #131   Overall #24   Document stores		Score 4.04 Rank #77   Overall #6   Wide column stores	Score 0.03 Rank #390   Overall #7   Native XML DBMS #24   Search engines
Website	aws.amazon.com/­documentdb	atos.net/en/convergence-creators/portfolio/standard-common-repository	azure.microsoft.com/­en-us/­services/­storage/­tables	www.searchxml.net/­category/­products
Technical documentation	aws.amazon.com/­documentdb/­resources			www.searchxml.net/­support/­handouts
Developer		Atos Convergence Creators	Microsoft	informationpartners gmbh
Initial release	2019	2016	2012	2015
Current release		1703		1.0
License Commercial or Open Source	commercial	commercial	commercial	commercial
Cloud-based only Only available as a cloud service	yes	no	yes	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language		Java		C++
Server operating systems	hosted	Linux	hosted	Windows
Data scheme	schema-free	Schema and schema-less with LDAP views	schema-free	schema-free
Typing predefined data types such as float or date	yes	optional	yes	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.	no	yes	no	yes
Secondary indexes	yes	yes	no	yes
SQL Support of SQL	no	no	no	no
APIs and other access methods	proprietary protocol using JSON (MongoDB compatible)	LDAP	RESTful HTTP API	RESTful HTTP API WebDAV XQuery XSLT
Supported programming languages	Go Java JavaScript (Node.js) PHP Python	All languages with LDAP bindings	.Net C# C++ Java JavaScript (Node.js) PHP Python Ruby	C++ most other programming languages supported via APIs
Server-side scripts Stored procedures	no	no	no	yes on the application server
Triggers	no	yes	no	no
Partitioning methods Methods for storing different data on different nodes	none	Sharding cell division	Sharding Implicit feature of the cloud service	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	yes implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.	yes sychronisation to multiple collections
MapReduce Offers an API for user-defined Map/Reduce methods	no may be implemented via Amazon Elastic MapReduce (Amazon EMR)		no	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency	Immediate Consistency or Eventual Consistency depending on configuration	Immediate Consistency	Immediate Consistency
Foreign keys Referential integrity	no typically not used, however similar functionality with DBRef possible	no	no	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic single-document operations	Atomic execution of specific operations	optimistic locking	multiple readers, single writer
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	yes	yes	yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.		yes	no	no
User concepts Access control	Access rights for users and roles	LDAP bind authentication	Access rights based on private key authentication or shared access signatures	Domain, group and role-based access control at the document level and for application services
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More resources
	Amazon DocumentDB	Atos Standard Common Repository	Microsoft Azure Table Storage	searchxml
Recent citations in the news	AWS announces Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service 16 May 2024, AWS Blog Use LangChain and vector search on Amazon DocumentDB to build a generative AI chatbot | Amazon Web Services 20 May 2024, AWS Blog Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services 29 November 2023, AWS Blog AWS announces Amazon DocumentDB I/O-Optimized 21 November 2023, AWS Blog Use headless clusters in Amazon DocumentDB for cost-effective multi-Region resiliency | Amazon Web Services 8 March 2024, AWS Blog provided by Google News		Working with Azure to Use and Manage Data Lakes 7 March 2024, Simplilearn How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB 9 July 2021, hackernoon.com How to use Azure Table storage in .Net 14 January 2019, InfoWorld How to write data to Azure Table Store with an Azure Function 14 April 2017, Experts Exchange Inside Azure File Storage 7 October 2015, Microsoft provided by Google News

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