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DBMS > Apache Phoenix vs. ClickHouse vs. Fauna vs. Microsoft Azure Data Explorer

Vergleich der Systemeigenschaften Apache Phoenix vs. ClickHouse vs. Fauna vs. Microsoft Azure Data Explorer

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NameApache Phoenix  Xaus Vergleich ausschliessenClickHouse  Xaus Vergleich ausschliessenFauna infopreviously named FaunaDB  Xaus Vergleich ausschliessenMicrosoft Azure Data Explorer  Xaus Vergleich ausschliessen
KurzbeschreibungA scale-out RDBMS with evolutionary schema built on Apache HBaseA high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Fully managed big data interactive analytics platform
Primäres DatenbankmodellRelational DBMSRelational DBMSDocument Store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMS infocolumn oriented
Sekundäre DatenbankmodelleTime Series DBMSDocument 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
Punkte2,06
Rang#123  Overall
#58  Relational DBMS
Punkte15,55
Rang#38  Overall
#23  Relational DBMS
Punkte1,55
Rang#151  Overall
#26  Document Stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Punkte3,80
Rang#81  Overall
#43  Relational DBMS
Websitephoenix.apache.orgclickhouse.comfauna.comazure.microsoft.com/­services/­data-explorer
Technische Dokumentationphoenix.apache.orgclickhouse.com/­docsdocs.fauna.comdocs.microsoft.com/­en-us/­azure/­data-explorer
EntwicklerApache Software FoundationClickhouse Inc.Fauna, Inc.Microsoft
Erscheinungsjahr2014201620142019
Aktuelle Version5.0-HBase2, July 2018 and 4.15-HBase1, December 2019v24.4.2.141-stable, Juni 2024cloud service with continuous releases
Lizenz infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0kommerziellkommerziell
Ausschließlich ein Cloud-Service infoNur als Cloud-Service verfügbarneinneinjaja
DBaaS Angebote (gesponserte Links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
  • ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
  • Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
  • DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
ImplementierungsspracheJavaC++Scala
Server BetriebssystemeLinux
Unix
Windows
FreeBSD
Linux
macOS
gehostetgehostet
Datenschemaja infolate-bound, schema-on-read capabilitiesjaschemafreiFixed schema with schema-less datatypes (dynamic)
Typisierung infovordefinierte Datentypen, z.B. float oder datejajaneinja infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
XML Unterstützung infoVerarbeitung von Daten in XML Format, beispielsweise Speicherung von XML-Strukturen und/oder Unterstützung von XPath, XQuery, XSLTneinneinneinja
Sekundärindizesjayesjaall fields are automatically indexed
SQL infoSupport of SQLjaClose to ANSI SQL (SQL/JSON + extensions)neinKusto Query Language (KQL), SQL subset
APIs und andere ZugriffskonzepteJDBCgRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietäres Protokoll
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Unterstützte ProgrammiersprachenC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C# info3rd party library
C++
Elixir info3rd party library
Go info3rd party library
Java info3rd party library
JavaScript (Node.js) info3rd party library
Kotlin info3rd party library
Nim info3rd party library
Perl info3rd party library
PHP info3rd party library
Python info3rd party library
R info3rd party library
Ruby info3rd party library
Rust
Scala info3rd party library
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-seitige Scripts infoStored Proceduresbenutzerdefinierte Funktionenjabenutzerdefinierte FunktionenYes, possible languages: KQL, Python, R
Triggersneinneinneinja infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitionierungsmechanismen infoMethoden zum Speichern von unterschiedlichen Daten auf unterschiedlichen KnotenShardingkey based and customhorizontale Partitionierung infoconsistent hashingSharding infoImplicit feature of the cloud service
Replikationsmechanismen infoMethoden zum redundanten Speichern von Daten auf mehreren KnotenMulti-Source Replikation
Source-Replica Replikation
Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.Multi-Source Replikationja infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoBietet ein API für Map/Reduce OperationenHadoop integrationneinneinSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Konsistenzkonzept infoMethoden zur Sicherstellung der Konsistenz in einem verteilten SystemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Fremdschlüssel inforeferenzielle Integritätneinneinjanein
Transaktionskonzept infoUnterstützung zur Sicherstellung der Datenintegrität bei nicht-atomaren DatenmanipulationenACIDneinACIDnein
Concurrency infoUnterstützung von gleichzeitig ausgeführten Datenmanipulationenjajajaja
Durability infoDauerhafte Speicherung der Datenjajajaja
In-Memory Unterstützung infoGibt es Möglichkeiten einige oder alle Strukturen nur im Hauptspeicher zu haltenjajaneinnein
Berechtigungskonzept infoZugriffskontrolleAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.Identity management, authentication, and access controlAzure Active Directory Authentication

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Weitere Ressourcen
Apache PhoenixClickHouseFauna infopreviously named FaunaDBMicrosoft Azure Data Explorer
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