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DBMS > Amazon DocumentDB vs. AnzoGraph DB vs. FatDB vs. Microsoft Azure Table Storage vs. Yaacomo

System Properties Comparison Amazon DocumentDB vs. AnzoGraph DB vs. FatDB vs. Microsoft Azure Table Storage vs. Yaacomo

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAnzoGraph DB  Xexclude from comparisonFatDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonYaacomo  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationA .NET NoSQL DBMS that can integrate with and extend SQL Server.A Wide Column Store for rapid development using massive semi-structured datasetsOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument storeGraph DBMS
RDF store
Document store
Key-value store
Wide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Websiteaws.amazon.com/­documentdbcambridgesemantics.com/­anzographazure.microsoft.com/­en-us/­services/­storage/­tablesyaacomo.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htm
DeveloperCambridge SemanticsFatCloudMicrosoftQ2WEB GmbH
Initial release20192018201220122009
Current release2.3, January 2021
License infoCommercial or Open Sourcecommercialcommercial infofree trial version availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#
Server operating systemshostedLinuxWindowshostedAndroid
Linux
Windows
Data schemeschema-freeSchema-free and OWL/RDFS-schema supportschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLnoSPARQL and SPARQL* as primary query language. Cypher preview.no infoVia inetgration in SQL Servernoyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
RESTful HTTP APIJDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C++
Java
Python
C#.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes infovia applicationsno
Triggersnonoyes infovia applicationsnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic shardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication in MPP-Clusterselectable replication factoryes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Kerberos/HDFS data loadingyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in MPP-ClusterEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleno infonot needed in graphsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDnooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and rolesno infoCan implement custom security layer via applicationsAccess rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBAnzoGraph DBFatDBMicrosoft Azure Table StorageYaacomo
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