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DBMS > GridDB vs. Microsoft Azure Table Storage vs. Sadas Engine vs. Sphinx

System Properties Comparison GridDB vs. Microsoft Azure Table Storage vs. Sadas Engine vs. Sphinx

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSadas Engine  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataA Wide Column Store for rapid development using massive semi-structured datasetsSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSWide column storeRelational DBMSSearch engine
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitegriddb.netazure.microsoft.com/­en-us/­services/­storage/­tableswww.sadasengine.comsphinxsearch.com
Technical documentationdocs.griddb.netwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationsphinxsearch.com/­docs
DeveloperToshiba CorporationMicrosoftSADAS s.r.l.Sphinx Technologies Inc.
Initial release2013201220062001
Current release5.1, August 20228.03.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercial infofree trial version availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C++
Server operating systemsLinuxhostedAIX
Linux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyesno
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 indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noyesSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
Proprietary protocol
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnononono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container leveloptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnoyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights based on private key authentication or shared access signaturesAccess rights for users, groups and roles according to SQL-standardno
More information provided by the system vendor
GridDBMicrosoft Azure Table StorageSadas EngineSphinx
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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More resources
GridDBMicrosoft Azure Table StorageSadas EngineSphinx
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