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DBMS > GridDB vs. Microsoft Azure Data Explorer vs. Sadas Engine vs. Teradata Aster vs. TimescaleDB

Vergleich der Systemeigenschaften GridDB vs. Microsoft Azure Data Explorer vs. Sadas Engine vs. Teradata Aster vs. TimescaleDB

Redaktionelle Informationen bereitgestellt von DB-Engines
NameGridDB  Xaus Vergleich ausschliessenMicrosoft Azure Data Explorer  Xaus Vergleich ausschliessenSadas Engine  Xaus Vergleich ausschliessenTeradata Aster  Xaus Vergleich ausschliessenTimescaleDB  Xaus Vergleich ausschliessen
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
KurzbeschreibungScalable in-memory time series database optimized for IoT and Big DataFully managed big data interactive analytics platformSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsPlatform for big data analytics on multistructured data sources and typesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primäres DatenbankmodellTime Series DBMSRelational DBMS infocolumn orientedRelational DBMSRelational DBMSTime Series DBMS
Sekundäre DatenbankmodelleKey-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
Suchmaschine 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
Relational DBMS
DB-Engines Ranking infomisst die Popularität von Datenbankmanagement- systemenranking trend
Trend Chart
Punkte2,02
Rang#132  Overall
#11  Time Series DBMS
Punkte5,16
Rang#69  Overall
#37  Relational DBMS
Punkte0,03
Rang#379  Overall
#156  Relational DBMS
Punkte4,87
Rang#74  Overall
#4  Time Series DBMS
Websitegriddb.netazure.microsoft.com/­services/­data-explorerwww.sadasengine.comwww.timescale.com
Technische Dokumentationdocs.griddb.netdocs.microsoft.com/­en-us/­azure/­data-explorerwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationdocs.timescale.com
EntwicklerToshiba CorporationMicrosoftSADAS s.r.l.TeradataTimescale
Erscheinungsjahr20132019200620052017
Aktuelle Version5.1, August 2022cloud service with continuous releases8.02.13.0, November 2023
Lizenz infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablekommerziellkommerziell infofree trial version availablekommerziellOpen Source infoApache 2.0
Ausschließlich ein Cloud-Service infoNur als Cloud-Service verfügbarneinjaneinneinnein
DBaaS Angebote (gesponserte Links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
ImplementierungsspracheC++C++C
Server BetriebssystemeLinuxgehostetAIX
Linux
Windows
LinuxLinux
OS X
Windows
DatenschemajaFixed schema with schema-less datatypes (dynamic)jaFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeja
Typisierung infovordefinierte Datentypen, z.B. float oder dateja infonumerical, string, blob, geometry, boolean, timestampja infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesjajaja
XML Unterstützung infoVerarbeitung von Daten in XML Format, beispielsweise Speicherung von XML-Strukturen und/oder Unterstützung von XPath, XQuery, XSLTneinjaneinja infoin Aster File Storeja
Sekundärindizesjaall fields are automatically indexedjajaja
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)Kusto Query Language (KQL), SQL subsetjajaja infofull PostgreSQL SQL syntax
APIs und andere ZugriffskonzepteJDBC
ODBC
Proprietäres Protokoll
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Proprietäres Protokoll
ADO.NET
JDBC
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Unterstützte ProgrammiersprachenC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Groovy
Java
PHP
Python
C
C#
C++
Java
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-seitige Scripts infoStored ProceduresneinYes, possible languages: KQL, Python, RneinR packagesbenutzerdefinierte Funktionen, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersjaja infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyneinneinja
Partitionierungsmechanismen infoMethoden zum Speichern von unterschiedlichen Daten auf unterschiedlichen KnotenShardingSharding infoImplicit feature of the cloud servicehorizontale PartitionierungShardingyes, across time and space (hash partitioning) attributes
Replikationsmechanismen infoMethoden zum redundanten Speichern von Daten auf mehreren KnotenSource-Replica Replikationja infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.keineja infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.Source-Replica Replikation info
MapReduce infoBietet ein API für Map/Reduce OperationenConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkneinja infoSQL Map-Reduce Frameworknein
Konsistenzkonzept infoMethoden zur Sicherstellung der Konsistenz in einem verteilten SystemImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Fremdschlüssel inforeferenzielle Integritätneinneinjaneinja
Transaktionskonzept infoUnterstützung zur Sicherstellung der Datenintegrität bei nicht-atomaren DatenmanipulationenACID at container levelneinACIDACID
Concurrency infoUnterstützung von gleichzeitig ausgeführten Datenmanipulationenjajajajaja
Durability infoDauerhafte Speicherung der Datenjajajajaja
In-Memory Unterstützung infoGibt es Möglichkeiten einige oder alle Strukturen nur im Hauptspeicher zu haltenjaneinja infomanaged by 'Learn by Usage'neinnein
Berechtigungskonzept infoZugriffskontrolleAccess rights for users can be defined per databaseAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standardBenutzer mit feingranularem Berechtigungskonzept entsprechend SQL-StandardBenutzer mit feingranularem Berechtigungskonzept entsprechend SQL-Standard
Weitere Informationen bereitgestellt vom Systemhersteller
GridDBMicrosoft Azure Data ExplorerSadas EngineTeradata AsterTimescaleDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» mehr
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» mehr
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» mehr
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» mehr
Market metricsGitHub trending repository
» mehr
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» mehr

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Weitere Ressourcen
GridDBMicrosoft Azure Data ExplorerSadas EngineTeradata AsterTimescaleDB
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16. Januar 2024, global.toshiba

General Availability of GridDB 5.3 Enterprise Edition ~ Major Enhancement in IoT and Time Series Data Analysis ...
16. Mai 2023, global.toshiba

Toshiba launches cloudy managed IoT database service running its own GridDB
8. April 2021, The Register

GridDB Use case Large-scale high-speed processing of smart meter data following the deregulation of electrical power ...
1. November 2020, global.toshiba

Toshiba's Distributed Database GridDB(R) Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data ...
3. Dezember 2019, global.toshiba

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bereitgestellt von Google News



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