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DBMS > FeatureBase vs. Kinetica vs. Microsoft Azure Data Explorer vs. RDF4J

System Properties Comparison FeatureBase vs. Kinetica vs. Microsoft Azure Data Explorer vs. RDF4J

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Editorial information provided by DB-Engines
NameFeatureBase  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Fully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedRDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
Document 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
Search engine 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 infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websitewww.featurebase.comwww.kinetica.comazure.microsoft.com/­services/­data-explorerrdf4j.org
Technical documentationdocs.featurebase.comdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorerrdf4j.org/­documentation
DeveloperMolecula and Pilosa Open Source ContributorsKineticaMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2017201220192004
Current release2022, May 20227.1, August 2021cloud service with continuous releases
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC, C++Java
Server operating systemsLinux
macOS
LinuxhostedLinux
OS X
Unix
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyes
Secondary indexesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL queriesSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetno
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesJava
Python
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsYes, possible languages: KQL, Python, Ryes
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes, using Linux fsyncyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and roles on table levelAzure Active Directory Authenticationno

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FeatureBaseKineticaMicrosoft Azure Data ExplorerRDF4J infoformerly known as Sesame
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