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DBMS > Amazon DocumentDB vs. Microsoft Azure AI Search vs. Spark SQL vs. TigerGraph

System Properties Comparison Amazon DocumentDB vs. Microsoft Azure AI Search vs. Spark SQL vs. TigerGraph

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceSearch-as-a-service for web and mobile app developmentSpark SQL is a component on top of 'Spark Core' for structured data processingA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument storeSearch engineRelational DBMSGraph DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score5.52
Rank#59  Overall
#6  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Websiteaws.amazon.com/­documentdbazure.microsoft.com/­en-us/­services/­searchspark.apache.org/­sqlwww.tigergraph.com
Technical documentationaws.amazon.com/­documentdb/­resourceslearn.microsoft.com/­en-us/­azure/­searchspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.com
DeveloperMicrosoftApache Software Foundation
Initial release2019201520142017
Current releaseV13.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++
Server operating systemshostedhostedLinux
OS X
Windows
Linux
Data schemeschema-freeyesyesyes
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 indexesyesyesno
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsSQL-like query language (GSQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)RESTful HTTP APIJDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
Java
JavaScript
Python
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnononoyes
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users and rolesyes infousing Azure authenticationnoRole-based access control

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More resources
Amazon DocumentDBMicrosoft Azure AI SearchSpark SQLTigerGraph
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