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DBMS > BigObject vs. GridDB vs. Microsoft Azure AI Search vs. Sphinx

System Properties Comparison BigObject vs. GridDB vs. Microsoft Azure AI Search vs. Sphinx

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesScalable in-memory time series database optimized for IoT and Big DataSearch-as-a-service for web and mobile app developmentOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedTime Series DBMSSearch engineSearch engine
Secondary database modelsKey-value store
Relational DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Websitebigobject.iogriddb.netazure.microsoft.com/­en-us/­services/­searchsphinxsearch.com
Technical documentationdocs.bigobject.iodocs.griddb.netlearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docs
DeveloperBigObject, Inc.Toshiba CorporationMicrosoftSphinx Technologies Inc.
Initial release2015201320152001
Current release5.1, August 2022V13.5.1, February 2023
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesno
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.nonono
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)noSQL-like query language (SphinxQL)
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP APIProprietary protocol
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresLuanonono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding 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 nodesnoneSource-replica replicationyes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelnono
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlnoAccess rights for users can be defined per databaseyes infousing Azure authenticationno
More information provided by the system vendor
BigObjectGridDBMicrosoft Azure AI SearchSphinx
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
BigObjectGridDBMicrosoft Azure AI SearchSphinx
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