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DBMS > GridDB vs. Microsoft Azure Data Explorer vs. Sequoiadb vs. Teradata vs. TimesTen

System Properties Comparison GridDB vs. Microsoft Azure Data Explorer vs. Sequoiadb vs. Teradata vs. TimesTen

Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSequoiadb  Xexclude from comparisonTeradata  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataFully managed big data interactive analytics platformNewSQL database with distributed OLTP and SQLA hybrid cloud data analytics software platform (Teradata Vantage)In-Memory RDBMS compatible to Oracle
Primary database modelTime Series DBMSRelational DBMS infocolumn orientedDocument store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Document store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websitegriddb.netazure.microsoft.com/­services/­data-explorerwww.sequoiadb.comwww.teradata.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.griddb.netdocs.microsoft.com/­en-us/­azure/­data-explorerwww.sequoiadb.com/­en/­index.php?m=Files&a=indexdocs.teradata.comdocs.oracle.com/­database/­timesten-18.1
DeveloperToshiba CorporationMicrosoftSequoiadb Ltd.TeradataOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20132019201319841998
Current release5.1, August 2022cloud service with continuous releasesTeradata Vantage 1.0 MU2, January 201911 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoServer: AGPL; Client: Apache V2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemsLinuxhostedLinuxhosted
Linux
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)schema-freeyesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infooid, date, timestamp, binary, regexyesyes
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.noyesnoyesno
Secondary indexesyesall fields are automatically indexedyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)Kusto Query Language (KQL), SQL subsetSQL-like query languageyes infoSQL 2016 + extensionsyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
proprietary protocol using JSON.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C++
Java
PHP
Python
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, RJavaScriptyes infoUDFs, stored procedures, table functions in parallelPL/SQL
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardingSharding infoHashingnone
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.Source-replica replicationMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoDocument is locked during a transactionACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyesyes
User concepts infoAccess controlAccess rights for users can be defined per databaseAzure Active Directory Authenticationsimple password-based access controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
GridDBMicrosoft Azure Data ExplorerSequoiadbTeradataTimesTen
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 Data ExplorerSequoiadbTeradataTimesTen
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