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DBMS > Faircom DB vs. Kdb vs. Microsoft Azure Data Explorer vs. RDF4J

System Properties Comparison Faircom DB vs. Kdb vs. Microsoft Azure Data Explorer vs. RDF4J

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Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonKdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.High performance Time Series DBMSFully 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 modelKey-value store
Relational DBMS
Time Series DBMS
Vector DBMS
Relational DBMS infocolumn orientedRDF store
Secondary database modelsRelational 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
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
Score0.18
Rank#314  Overall
#45  Key-value stores
#141  Relational DBMS
Score7.73
Rank#45  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score0.72
Rank#222  Overall
#9  RDF stores
Websitewww.faircom.com/­products/­faircom-dbkx.comazure.microsoft.com/­services/­data-explorerrdf4j.org
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlcode.kx.comdocs.microsoft.com/­en-us/­azure/­data-explorerrdf4j.org/­documentation
DeveloperFairCom CorporationKx Systems, a division of First Derivatives plcMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release19792000 infokdb was released 2000, kdb+ in 200320192004
Current releaseV13, July 20243.6, May 2018cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercial infofree 32-bit versioncommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++qJava
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Unix
Windows
Data schemeschema free, schema optional, schema required, partial schema,yesFixed schema with schema-less datatypes (dynamic)yes infoRDF Schemas
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyesyes 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.noyesyes
Secondary indexesyesyes infotable attribute 'grouped'all fields are automatically indexedyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsSQL-like query language (q)Kusto Query Language (KQL), SQL subsetno
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
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 languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
PHP
Python
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++user defined functionsYes, possible languages: KQL, Python, Ryes
Triggersyesyes infowith viewsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioninghorizontal partitioningSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Source-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 methodsnono infosimilar paradigm used for internal processingSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentnonoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyesyes 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.yesyesno
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesrights management via user accountsAzure Active Directory Authenticationno
More information provided by the system vendor
Faircom DB infoformerly c-treeACEKdbMicrosoft Azure Data ExplorerRDF4J infoformerly known as Sesame
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
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More resources
Faircom DB infoformerly c-treeACEKdbMicrosoft Azure Data ExplorerRDF4J infoformerly known as Sesame
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