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DBMS > Apache Pinot vs. eXtremeDB vs. Microsoft Azure Data Explorer vs. Oracle NoSQL vs. Sadas Engine

Vergleich der Systemeigenschaften Apache Pinot vs. eXtremeDB vs. Microsoft Azure Data Explorer vs. Oracle NoSQL vs. Sadas Engine

Redaktionelle Informationen bereitgestellt von DB-Engines
NameApache Pinot  Xaus Vergleich ausschliesseneXtremeDB  Xaus Vergleich ausschliessenMicrosoft Azure Data Explorer  Xaus Vergleich ausschliessenOracle NoSQL  Xaus Vergleich ausschliessenSadas Engine  Xaus Vergleich ausschliessen
KurzbeschreibungRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyNatively in-memory DBMS with options for persistency, high-availability and clusteringFully managed big data interactive analytics platformA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodesSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primäres DatenbankmodellRelational DBMSRelational DBMS
Time Series DBMS
Relational DBMS infocolumn orientedDocument Store
Key-Value Store
Relational DBMS
Relational 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
Punkte0,40
Rang#270  Overall
#125  Relational DBMS
Punkte0,74
Rang#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Punkte4,38
Rang#77  Overall
#41  Relational DBMS
Punkte2,95
Rang#100  Overall
#17  Document Stores
#17  Key-Value Stores
#50  Relational DBMS
Punkte0,00
Rang#383  Overall
#158  Relational DBMS
Websitepinot.apache.orgwww.mcobject.comazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­nosql/­technologies/­nosqlwww.sadasengine.com
Technische Dokumentationdocs.pinot.apache.orgwww.mcobject.com/­docs/­extremedb.htmdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.htmlwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
EntwicklerApache Software Foundation and contributorsMcObjectMicrosoftOracleSADAS s.r.l.
Erscheinungsjahr20152001201920112006
Aktuelle Version1.0.0, September 20238.2, 2021cloud service with continuous releases23.3, Dezember 20238.0
Lizenz infoCommercial or Open SourceOpen Source infoApache Version 2.0kommerziellkommerziellOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)kommerziell infofree trial version available
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.
ImplementierungsspracheJavaC und C++JavaC++
Server BetriebssystemeAll OS with a Java JDK11 or higherAIX
HP-UX
Linux
macOS
Solaris
Windows
gehostetLinux
Solaris SPARC/x86
AIX
Linux
Windows
DatenschemajajaFixed schema with schema-less datatypes (dynamic)Support Fixed schema and Schema-less deployment with the ability to interoperate between them.ja
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-typesoptionalja
XML Unterstützung infoVerarbeitung von Daten in XML Format, beispielsweise Speicherung von XML-Strukturen und/oder Unterstützung von XPath, XQuery, XSLTnein infosupport of XML interfaces availablejaneinnein
Sekundärindizesjaall fields are automatically indexedjaja
SQL infoSupport of SQLSQL-like query languageja infowith the option: eXtremeSQLKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statementsja
APIs und andere ZugriffskonzepteJDBC.NET Client API
JDBC
JNI
ODBC
Proprietäres Protokoll
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Proprietäres Protokoll
Unterstützte ProgrammiersprachenGo
Java
Python
.Net
C
C#
C++
Java
Lua
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-seitige Scripts infoStored ProceduresjaYes, possible languages: KQL, Python, Rneinnein
Triggersja infoby defining eventsja infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyneinnein
Partitionierungsmechanismen infoMethoden zum Speichern von unterschiedlichen Daten auf unterschiedlichen Knotenhorizontal partitioninghorizontale Partitionierung / shardingSharding infoImplicit feature of the cloud serviceShardinghorizontale Partitionierung
Replikationsmechanismen infoMethoden zum redundanten Speichern von Daten auf mehreren KnotenActive Replication Fabric™ for IoT
Multi-Source Replikation infoby means of eXtremeDB Cluster option
Source-Replica Replikation infoby means of eXtremeDB High Availability option
ja infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Electable source-replica replication per shard. Support distributed global deployment with Multi-region table featurekeine
MapReduce infoBietet ein API für Map/Reduce OperationenneinSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integrationnein
Konsistenzkonzept infoMethoden zur Sicherstellung der Konsistenz in einem verteilten SystemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency infoabhängig von Konfiguration
Immediate Consistency
Fremdschlüssel inforeferenzielle Integritätjaneinneinja
Transaktionskonzept infoUnterstützung zur Sicherstellung der Datenintegrität bei nicht-atomaren DatenmanipulationenACIDneinkonfigurierbar infoACID innerhalb eines 'storage nodes' (=shard)
Concurrency infoUnterstützung von gleichzeitig ausgeführten Datenmanipulationenja infoOptimistic (MVCC) and pessimistic (locking) strategies availablejajaja
Durability infoDauerhafte Speicherung der Datenjajajaja
In-Memory Unterstützung infoGibt es Möglichkeiten einige oder alle Strukturen nur im Hauptspeicher zu haltenjaneinja infooff heap cacheja infomanaged by 'Learn by Usage'
Berechtigungskonzept infoZugriffskontrolleAzure Active Directory AuthenticationZugriffsrechte für Benutzer und RollenAccess rights for users, groups and roles according to SQL-standard
Weitere Informationen bereitgestellt vom Systemhersteller
Apache PinoteXtremeDBMicrosoft Azure Data ExplorerOracle NoSQLSadas Engine
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» mehr
Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» mehr
Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» mehr
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» mehr
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» mehr
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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Weitere Ressourcen
Apache PinoteXtremeDBMicrosoft Azure Data ExplorerOracle NoSQLSadas Engine
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