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DBMS > Amazon DocumentDB vs. Microsoft Azure AI Search vs. Splice Machine

System Properties Comparison Amazon DocumentDB vs. Microsoft Azure AI Search vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceSearch-as-a-service for web and mobile app developmentOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeSearch engineRelational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score5.59
Rank#63  Overall
#7  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­documentdbazure.microsoft.com/­en-us/­services/­searchsplicemachine.com
Technical documentationaws.amazon.com/­documentdb/­resourceslearn.microsoft.com/­en-us/­azure/­searchsplicemachine.com/­how-it-works
DeveloperMicrosoftSplice Machine
Initial release201920152014
Current releaseV13.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nono
Secondary indexesyesyesyes
SQL infoSupport of SQLnonoyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
Java
JavaScript
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infoJava
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
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 serviceMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users and rolesyes infousing Azure authenticationAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DocumentDBMicrosoft Azure AI SearchSplice Machine
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