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DBMS > Apache Druid vs. Faircom DB vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. NSDb

Vergleich der Systemeigenschaften Apache Druid vs. Faircom DB vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. NSDb

Redaktionelle Informationen bereitgestellt von DB-Engines
NameApache Druid  Xaus Vergleich ausschliessenFaircom DB infoformerly c-treeACE  Xaus Vergleich ausschliessenGoogle Cloud Bigtable  Xaus Vergleich ausschliessenMicrosoft Azure Data Explorer  Xaus Vergleich ausschliessenNSDb  Xaus Vergleich ausschliessen
KurzbeschreibungOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully managed big data interactive analytics platformScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primäres DatenbankmodellRelational DBMS
Time Series DBMS
Key-Value Store
Relational DBMS
Key-Value Store
Wide Column Store
Relational DBMS infocolumn orientedTime Series 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
Punkte3,25
Rang#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Punkte0,29
Rang#304  Overall
#43  Key-Value Stores
#136  Relational DBMS
Punkte3,15
Rang#95  Overall
#14  Key-Value Stores
#8  Wide Column Stores
Punkte3,80
Rang#81  Overall
#43  Relational DBMS
Punkte0,08
Rang#369  Overall
#40  Time Series DBMS
Websitedruid.apache.orgwww.faircom.com/­products/­faircom-dbcloud.google.com/­bigtableazure.microsoft.com/­services/­data-explorernsdb.io
Technische Dokumentationdruid.apache.org/­docs/­latest/­designdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlcloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­data-explorernsdb.io/­Architecture
EntwicklerApache Software Foundation and contributorsFairCom CorporationGoogleMicrosoft
Erscheinungsjahr20121979201520192017
Aktuelle Version29.0.1, April 2024V12, November 2020cloud service with continuous releases
Lizenz infoCommercial or Open SourceOpen Source infoApache license v2kommerziell infoRestricted, free version availablekommerziellkommerziellOpen Source infoApache Version 2.0
Ausschließlich ein Cloud-Service infoNur als Cloud-Service verfügbarneinneinjajanein
DBaaS Angebote (gesponserte Links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
ImplementierungsspracheJavaANSI C, C++Java, Scala
Server BetriebssystemeLinux
OS X
Unix
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
gehostetgehostetLinux
macOS
Datenschemaja infoschema-less columns are supportedschema free, schema optional, schema required, partial schema,schemafreiFixed schema with schema-less datatypes (dynamic)
Typisierung infovordefinierte Datentypen, z.B. float oder datejaja, ANSI Standard SQL Types, JSON, typed binary structuresneinja infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes: int, bigint, decimal, string
XML Unterstützung infoVerarbeitung von Daten in XML Format, beispielsweise Speicherung von XML-Strukturen und/oder Unterstützung von XPath, XQuery, XSLTneinneinneinjanein
Sekundärindizesjajaneinall fields are automatically indexedall fields are automatically indexed
SQL infoSupport of SQLSQL for queryingyes, ANSI SQL with proprietary extensionsneinKusto Query Language (KQL), SQL subsetSQL-like query language
APIs und andere ZugriffskonzepteJDBC
RESTful HTTP/JSON API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
gRPC
HTTP REST
WebSocket
Unterstützte ProgrammiersprachenClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Scala
Server-seitige Scripts infoStored Proceduresneinja info.Net, JavaScript, C/C++neinYes, possible languages: KQL, Python, Rnein
Triggersneinjaneinja infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitionierungsmechanismen infoMethoden zum Speichern von unterschiedlichen Daten auf unterschiedlichen KnotenSharding infomanual/auto, time-basedFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingSharding infoImplicit feature of the cloud serviceSharding
Replikationsmechanismen infoMethoden zum redundanten Speichern von Daten auf mehreren Knotenja, durch HDFS, S3 oder andere Storage Enginesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Internal replication in Colossus, and regional replication between two clusters in different zonesja infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoBietet ein API für Map/Reduce OperationenneinneinjaSpark connector (open source): github.com/­Azure/­azure-kusto-sparknein
Konsistenzkonzept infoMethoden zur Sicherstellung der Konsistenz in einem verteilten SystemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Eventual Consistency
Fremdschlüssel inforeferenzielle Integritätneinjaneinneinnein
Transaktionskonzept infoUnterstützung zur Sicherstellung der Datenintegrität bei nicht-atomaren Datenmanipulationenneintunable from ACID to Eventually ConsistentAtomic single-row operationsneinnein
Concurrency infoUnterstützung von gleichzeitig ausgeführten Datenmanipulationenjajajajaja
Durability infoDauerhafte Speicherung der DatenjaYes, tunable from durable to delayed durability to in-memoryjajaUsing Apache Lucene
In-Memory Unterstützung infoGibt es Möglichkeiten einige oder alle Strukturen nur im Hauptspeicher zu haltenneinjaneinnein
Berechtigungskonzept infoZugriffskontrolleRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory Authentication

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Weitere Ressourcen
Apache DruidFaircom DB infoformerly c-treeACEGoogle Cloud BigtableMicrosoft Azure Data ExplorerNSDb
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