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DBMS > GridDB vs. Microsoft Azure Synapse Analytics vs. Oracle Coherence vs. Sphinx

System Properties Comparison GridDB vs. Microsoft Azure Synapse Analytics vs. Oracle Coherence vs. Sphinx

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonOracle Coherence  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOracles in-memory data grid solutionOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSRelational DBMSKey-value storeSearch engine
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score22.71
Rank#30  Overall
#18  Relational DBMS
Score2.02
Rank#131  Overall
#22  Key-value stores
Score6.03
Rank#60  Overall
#6  Search engines
Websitegriddb.netazure.microsoft.com/­services/­synapse-analyticswww.oracle.com/­java/­coherencesphinxsearch.com
Technical documentationdocs.griddb.netdocs.microsoft.com/­azure/­synapse-analyticsdocs.oracle.com/­en/­middleware/­standalone/­coherencesphinxsearch.com/­docs
DeveloperToshiba CorporationMicrosoftOracleSphinx Technologies Inc.
Initial release2013201620072001
Current release5.1, August 202214.1, August 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercialOpen 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++JavaC++
Server operating systemsLinuxhostedAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
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 indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)yesnoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
JCache
JPA
RESTful HTTP API
Proprietary protocol
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
Java
PHP
.Net
C++
Java
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoTransact SQLnono
Triggersyesnoyes infoLive Eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, horizontal partitioningShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesyes, with selectable consistency levelnone
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 ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDconfigurableno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infooptionallyyes 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.yesyes
User concepts infoAccess controlAccess rights for users can be defined per databaseyesauthentification to access the cache via certificates or http basic authenticationno
More information provided by the system vendor
GridDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseOracle CoherenceSphinx
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
GridDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseOracle CoherenceSphinx
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