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DBMS > Google Cloud Bigtable vs. Manticore Search vs. Microsoft Azure AI Search vs. RDF4J

System Properties Comparison Google Cloud Bigtable vs. Manticore Search vs. Microsoft Azure AI Search vs. RDF4J

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Multi-storage database for search, including full-text search.Search-as-a-service for web and mobile app developmentRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelKey-value store
Wide column store
Search engineSearch engineRDF store
Secondary database modelsTime Series DBMS infousing the Manticore Columnar LibraryVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score0.23
Rank#301  Overall
#21  Search engines
Score5.75
Rank#58  Overall
#7  Search engines
Score0.72
Rank#222  Overall
#9  RDF stores
Websitecloud.google.com/­bigtablemanticoresearch.comazure.microsoft.com/­en-us/­services/­searchrdf4j.org
Technical documentationcloud.google.com/­bigtable/­docsmanual.manticoresearch.comlearn.microsoft.com/­en-us/­azure/­searchrdf4j.org/­documentation
DeveloperGoogleManticore SoftwareMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2015201720152004
Current release6.0, February 2023V1
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemshostedFreeBSD
Linux
macOS
Windows
hostedLinux
OS X
Unix
Windows
Data schemeschema-freeFixed schemayesyes infoRDF Schemas
Typing infopredefined data types such as float or datenoInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyesyes
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.noCan index from XMLno
Secondary indexesnoyes infofull-text index on all search fieldsyesyes
SQL infoSupport of SQLnoSQL-like query languagenono
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
RESTful HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C#
Java
JavaScript
Python
Java
PHP
Python
Server-side scripts infoStored proceduresnouser defined functionsnoyes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSynchronous replication based on Galera libraryyes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsyes infoisolated transactions for atomic changes and binary logging for safe writesnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Manticore index.yesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyes infousing Azure authenticationno

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More resources
Google Cloud BigtableManticore SearchMicrosoft Azure AI SearchRDF4J infoformerly known as Sesame
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