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DBMS > Faircom DB vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. NSDb vs. Sadas Engine

Vergleich der Systemeigenschaften Faircom DB vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. NSDb vs. Sadas Engine

Redaktionelle Informationen bereitgestellt von DB-Engines
NameFaircom DB infoformerly c-treeACE  Xaus Vergleich ausschliessenGoogle Cloud Bigtable  Xaus Vergleich ausschliessenMicrosoft Azure Data Explorer  Xaus Vergleich ausschliessenNSDb  Xaus Vergleich ausschliessenSadas Engine  Xaus Vergleich ausschliessen
KurzbeschreibungNative 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 KubernetesSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primäres DatenbankmodellKey-Value Store
Relational DBMS
Key-Value Store
Wide Column Store
Relational DBMS infocolumn orientedTime Series DBMSRelational 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
Punkte0,20
Rang#318  Overall
#48  Key-Value Stores
#141  Relational DBMS
Punkte3,26
Rang#92  Overall
#13  Key-Value Stores
#8  Wide Column Stores
Punkte4,38
Rang#77  Overall
#41  Relational DBMS
Punkte0,00
Rang#383  Overall
#41  Time Series DBMS
Punkte0,00
Rang#383  Overall
#158  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbcloud.google.com/­bigtableazure.microsoft.com/­services/­data-explorernsdb.iowww.sadasengine.com
Technische Dokumentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlcloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­data-explorernsdb.io/­Architecturewww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
EntwicklerFairCom CorporationGoogleMicrosoftSADAS s.r.l.
Erscheinungsjahr19792015201920172006
Aktuelle VersionV12, November 2020cloud service with continuous releases8.0
Lizenz infoCommercial or Open Sourcekommerziell infoRestricted, free version availablekommerziellkommerziellOpen Source infoApache Version 2.0kommerziell infofree trial version available
Ausschließlich ein Cloud-Service infoNur als Cloud-Service verfügbarneinjajaneinnein
DBaaS Angebote (gesponserte Links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
ImplementierungsspracheANSI C, C++Java, ScalaC++
Server BetriebssystemeAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
gehostetgehostetLinux
macOS
AIX
Linux
Windows
Datenschemaschema free, schema optional, schema required, partial schema,schemafreiFixed schema with schema-less datatypes (dynamic)ja
Typisierung infovordefinierte Datentypen, z.B. float oder dateja, 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, stringja
XML Unterstützung infoVerarbeitung von Daten in XML Format, beispielsweise Speicherung von XML-Strukturen und/oder Unterstützung von XPath, XQuery, XSLTneinneinjaneinnein
Sekundärindizesjaneinall fields are automatically indexedall fields are automatically indexedja
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsneinKusto Query Language (KQL), SQL subsetSQL-like query languageja
APIs und andere ZugriffskonzepteADO.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
JDBC
ODBC
Proprietäres Protokoll
Unterstützte Programmiersprachen.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
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-seitige Scripts infoStored Proceduresja info.Net, JavaScript, C/C++neinYes, possible languages: KQL, Python, Rneinnein
Triggersjaneinja infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynein
Partitionierungsmechanismen infoMethoden zum Speichern von unterschiedlichen Daten auf unterschiedlichen KnotenFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingSharding infoImplicit feature of the cloud serviceShardinghorizontale Partitionierung
Replikationsmechanismen infoMethoden zum redundanten Speichern von Daten auf mehreren Knotenyes, 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.keine
MapReduce infoBietet ein API für Map/Reduce OperationenneinjaSpark connector (open source): github.com/­Azure/­azure-kusto-sparkneinnein
Konsistenzkonzept infoMethoden zur Sicherstellung der Konsistenz in einem verteilten SystemEventual 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 ConsistencyImmediate Consistency
Fremdschlüssel inforeferenzielle Integritätjaneinneinneinja
Transaktionskonzept infoUnterstützung zur Sicherstellung der Datenintegrität bei nicht-atomaren Datenmanipulationentunable from ACID to Eventually ConsistentAtomic single-row operationsneinnein
Concurrency infoUnterstützung von gleichzeitig ausgeführten Datenmanipulationenjajajajaja
Durability infoDauerhafte Speicherung der DatenYes, tunable from durable to delayed durability to in-memoryjajaUsing Apache Luceneja
In-Memory Unterstützung infoGibt es Möglichkeiten einige oder alle Strukturen nur im Hauptspeicher zu haltenjaneinneinja infomanaged by 'Learn by Usage'
Berechtigungskonzept infoZugriffskontrolleFine 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 AuthenticationAccess rights for users, groups and roles according to SQL-standard

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Weitere Ressourcen
Faircom DB infoformerly c-treeACEGoogle Cloud BigtableMicrosoft Azure Data ExplorerNSDbSadas Engine
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