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DBMS > EXASOL vs. GigaSpaces vs. GridDB vs. Microsoft Azure Data Explorer vs. Sphinx

Vergleich der Systemeigenschaften EXASOL vs. GigaSpaces vs. GridDB vs. Microsoft Azure Data Explorer vs. Sphinx

Redaktionelle Informationen bereitgestellt von DB-Engines
NameEXASOL  Xaus Vergleich ausschliessenGigaSpaces  Xaus Vergleich ausschliessenGridDB  Xaus Vergleich ausschliessenMicrosoft Azure Data Explorer  Xaus Vergleich ausschliessenSphinx  Xaus Vergleich ausschliessen
KurzbeschreibungHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsScalable in-memory time series database optimized for IoT and Big DataFully managed big data interactive analytics platformOpen Source Suchmaschine zum Suchen in Daten aus verschiedenen Quellen, u.a. relationalen Datenbanken
Primäres DatenbankmodellRelational DBMSDocument Store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSRelational DBMS infocolumn orientedSuchmaschine
Sekundäre DatenbankmodelleGraph DBMS
Suchmaschine
Key-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
DB-Engines Ranking infomisst die Popularität von Datenbankmanagement- systemenranking trend
Trend Chart
Punkte1,99
Rang#124  Overall
#58  Relational DBMS
Punkte0,97
Rang#192  Overall
#32  Document Stores
#6  Object oriented DBMS
Punkte1,95
Rang#128  Overall
#10  Time Series DBMS
Punkte4,38
Rang#77  Overall
#41  Relational DBMS
Punkte5,98
Rang#56  Overall
#5  Suchmaschinen
Websitewww.exasol.comwww.gigaspaces.comgriddb.netazure.microsoft.com/­services/­data-explorersphinxsearch.com
Technische Dokumentationwww.exasol.com/­resourcesdocs.gigaspaces.com/­latest/­landing.htmldocs.griddb.netdocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docs
EntwicklerExasolGigaspaces TechnologiesToshiba CorporationMicrosoftSphinx Technologies Inc.
Erscheinungsjahr20002000201320192001
Aktuelle Version15.5, September 20205.1, August 2022cloud service with continuous releases3.5.1, Februar 2023
Lizenz infoCommercial or Open SourcekommerziellOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablekommerziellOpen Source infoGPL Version 2, kommerzielle Lizenz erhältlich
Ausschließlich ein Cloud-Service infoNur als Cloud-Service verfügbarneinneinneinjanein
DBaaS Angebote (gesponserte Links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
ImplementierungsspracheJava, C++, .NetC++C++
Server BetriebssystemeLinux
macOS
Solaris
Windows
LinuxgehostetFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
DatenschemajaschemafreijaFixed schema with schema-less datatypes (dynamic)ja
Typisierung infovordefinierte Datentypen, z.B. float oder datejajaja 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-typesnein
XML Unterstützung infoVerarbeitung von Daten in XML Format, beispielsweise Speicherung von XML-Strukturen und/oder Unterstützung von XPath, XQuery, XSLTneinnein infoXML can be used for describing objects metadataneinja
Sekundärindizesjajajaall fields are automatically indexedja infoFull-Text Index auf allen Suchfeldern
SQL infoSupport of SQLjaSQL-99 for query and DML statementsSQL92, SQL-like TQL (Toshiba Query Language)Kusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)
APIs und andere Zugriffskonzepte.Net
JDBC
ODBC
WebSocket
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
Proprietäres Protokoll
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietäres Protokoll
Unterstützte ProgrammiersprachenJava
Lua
Python
R
.Net
C++
Java
Python
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infoinoffizielle Client Library
Java
Perl infoinoffizielle Client Library
PHP
Python
Ruby infoinoffizielle Client Library
Server-seitige Scripts infoStored Proceduresbenutzerdefinierte FunktionenjaneinYes, possible languages: KQL, Python, Rnein
Triggersjajajaja infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynein
Partitionierungsmechanismen infoMethoden zum Speichern von unterschiedlichen Daten auf unterschiedlichen KnotenShardingShardingShardingSharding infoImplicit feature of the cloud serviceSharding infoAufteilung der Daten erfolgt manuell, Suchabfragen auf verteilten Index werden unterstützt.
Replikationsmechanismen infoMethoden zum redundanten Speichern von Daten auf mehreren KnotenMulti-Source Replikation infosynchronous or asynchronous
Source-Replica Replikation infosynchronous or asynchronous
Source-Replica Replikationja infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.keine
MapReduce infoBietet ein API für Map/Reduce Operationenja infoHadoop integrationja infoMap-Reduce pattern can be built with XAP task executorsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknein
Konsistenzkonzept infoMethoden zur Sicherstellung der Konsistenz in einem verteilten SystemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Fremdschlüssel inforeferenzielle Integritätjaneinneinneinnein
Transaktionskonzept infoUnterstützung zur Sicherstellung der Datenintegrität bei nicht-atomaren DatenmanipulationenACIDACIDACID at container levelneinnein
Concurrency infoUnterstützung von gleichzeitig ausgeführten Datenmanipulationenjajajajaja
Durability infoDauerhafte Speicherung der Datenjajajajaja infoDer Originalinhalt von Feldern wird nicht im Sphinx-Index gespeichert.
In-Memory Unterstützung infoGibt es Möglichkeiten einige oder alle Strukturen nur im Hauptspeicher zu haltenjajajanein
Berechtigungskonzept infoZugriffskontrolleAccess rights for users, groups and roles according to SQL-standardRole-based access controlAccess rights for users can be defined per databaseAzure Active Directory Authenticationnein
Weitere Informationen bereitgestellt vom Systemhersteller
EXASOLGigaSpacesGridDBMicrosoft Azure Data ExplorerSphinx
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
EXASOLGigaSpacesGridDBMicrosoft Azure Data ExplorerSphinx
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