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DBMS > Google Cloud Bigtable vs. Microsoft Azure AI Search vs. Sphinx vs. Typesense

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure AI Search vs. Sphinx vs. Typesense

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  Xexclude from comparisonTypesense  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.Search-as-a-service for web and mobile app developmentOpen source search engine for searching in data from different sources, e.g. relational databasesA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelKey-value store
Wide column store
Search engineSearch engineSearch engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.52
Rank#59  Overall
#6  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Score0.76
Rank#219  Overall
#14  Search engines
Websitecloud.google.com/­bigtableazure.microsoft.com/­en-us/­services/­searchsphinxsearch.comtypesense.org
Technical documentationcloud.google.com/­bigtable/­docslearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docstypesense.org/­docs
DeveloperGoogleMicrosoftSphinx Technologies Inc.
Initial release2015201520012015
Current releaseV13.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemshostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesyesschema-free infopre-defined schema optional
Typing infopredefined data types such as float or datenoyesnoyes
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 indexesnoyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnonoSQL-like query language (SphinxQL)no
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIProprietary protocolRESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresnononono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoImplicit feature of the cloud servicenoneMulti-source replication using RAFT
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 integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infousing Azure authenticationno

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More resources
Google Cloud BigtableMicrosoft Azure AI SearchSphinxTypesense
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