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DBMS > GridGain vs. IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. Teradata Aster vs. TinkerGraph

Vergleich der Systemeigenschaften GridGain vs. IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. Teradata Aster vs. TinkerGraph

Redaktionelle Informationen bereitgestellt von DB-Engines
NameGridGain  Xaus Vergleich ausschliessenIBM Db2 Event Store  Xaus Vergleich ausschliessenMicrosoft Azure Data Explorer  Xaus Vergleich ausschliessenTeradata Aster  Xaus Vergleich ausschliessenTinkerGraph  Xaus Vergleich ausschliessen
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
KurzbeschreibungGridGain is an in-memory computing platform, built on Apache IgniteDistributed Event Store optimized for Internet of Things use casesFully managed big data interactive analytics platformPlatform for big data analytics on multistructured data sources and typesA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primäres DatenbankmodellKey-Value Store
Relational DBMS
Event Store
Time Series DBMS
Relational DBMS infocolumn orientedRelational DBMSGraph DBMS
Sekundäre DatenbankmodelleDocument 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
Punkte1,47
Rang#154  Overall
#26  Key-Value Stores
#72  Relational DBMS
Punkte0,19
Rang#323  Overall
#2  Event Stores
#28  Time Series DBMS
Punkte4,38
Rang#77  Overall
#41  Relational DBMS
Punkte0,08
Rang#348  Overall
#35  Graph DBMS
Websitewww.gridgain.comwww.ibm.com/­products/­db2-event-storeazure.microsoft.com/­services/­data-explorertinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technische Dokumentationwww.gridgain.com/­docs/­index.htmlwww.ibm.com/­docs/­en/­db2-event-storedocs.microsoft.com/­en-us/­azure/­data-explorer
EntwicklerGridGain Systems, Inc.IBMMicrosoftTeradata
Erscheinungsjahr20072017201920052009
Aktuelle VersionGridGain 8.5.12.0cloud service with continuous releases
Lizenz infoCommercial or Open Sourcekommerziellkommerziell infofree developer edition availablekommerziellkommerziellOpen Source infoApache 2.0
Ausschließlich ein Cloud-Service infoNur als Cloud-Service verfügbarneinneinjaneinnein
DBaaS Angebote (gesponserte Links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
ImplementierungsspracheJava, C++, .NetC und C++Java
Server BetriebssystemeLinux
OS X
Solaris
Windows
Linux infoLinux, macOS, Windows for the developer additiongehostetLinux
DatenschemajajaFixed schema with schema-less datatypes (dynamic)Flexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeschemafrei
Typisierung infovordefinierte Datentypen, z.B. float oder datejajaja infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesjaja
XML Unterstützung infoVerarbeitung von Daten in XML Format, beispielsweise Speicherung von XML-Strukturen und/oder Unterstützung von XPath, XQuery, XSLTjaneinjaja infoin Aster File Storenein
Sekundärindizesjaneinall fields are automatically indexedjanein
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLja infothrough the embedded Spark runtimeKusto Query Language (KQL), SQL subsetjanein
APIs und andere ZugriffskonzepteHDFS API
Hibernate
JCache
JDBC
ODBC
Propriätäres Protokoll
RESTful HTTP API
Spring Data
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
TinkerPop 3
Unterstützte ProgrammiersprachenC#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Java
Python
R
Groovy
Java
Server-seitige Scripts infoStored Proceduresyes (compute grid and cache interceptors can be used instead)jaYes, possible languages: KQL, Python, RR packagesnein
Triggersyes (cache interceptors and events)neinja infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyneinnein
Partitionierungsmechanismen infoMethoden zum Speichern von unterschiedlichen Daten auf unterschiedlichen KnotenShardingShardingSharding infoImplicit feature of the cloud serviceShardingkeine
Replikationsmechanismen infoMethoden zum redundanten Speichern von Daten auf mehreren Knotenyes (replicated cache)Active-active shard replicationja infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.ja infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.keine
MapReduce infoBietet ein API für Map/Reduce Operationenyes (compute grid and hadoop accelerator)neinSpark connector (open source): github.com/­Azure/­azure-kusto-sparkja infoSQL Map-Reduce Frameworknein
Konsistenzkonzept infoMethoden zur Sicherstellung der Konsistenz in einem verteilten SystemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configurationkeine
Fremdschlüssel inforeferenzielle Integritätneinneinneinneinja infoRelationships in graphs
Transaktionskonzept infoUnterstützung zur Sicherstellung der Datenintegrität bei nicht-atomaren DatenmanipulationenACIDneinneinACIDnein
Concurrency infoUnterstützung von gleichzeitig ausgeführten DatenmanipulationenjaNo - written data is immutablejajanein
Durability infoDauerhafte Speicherung der DatenjaYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storagejajaoptional
In-Memory Unterstützung infoGibt es Möglichkeiten einige oder alle Strukturen nur im Hauptspeicher zu haltenjajaneinneinja
Berechtigungskonzept infoZugriffskontrolleSecurity Hooks for custom implementationsBenutzer mit feingranularem Berechtigungskonzept entsprechend SQL-StandardAzure Active Directory AuthenticationBenutzer mit feingranularem Berechtigungskonzept entsprechend SQL-Standardnein

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Weitere Ressourcen
GridGainIBM Db2 Event StoreMicrosoft Azure Data ExplorerTeradata AsterTinkerGraph
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