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DBMS > Kdb vs. Microsoft Azure Data Explorer vs. Oracle vs. Sphinx vs. Vitess

System Properties Comparison Kdb vs. Microsoft Azure Data Explorer vs. Oracle vs. Sphinx vs. Vitess

Editorial information provided by DB-Engines
NameKdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle  Xexclude from comparisonSphinx  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionHigh performance Time Series DBMSFully managed big data interactive analytics platformWidely used RDBMSOpen source search engine for searching in data from different sources, e.g. relational databasesScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelTime Series DBMS
Vector DBMS
Relational DBMS infocolumn orientedRelational DBMSSearch engineRelational DBMS
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
Document store
Graph DBMS infowith Oracle Spatial and Graph
RDF store infowith Oracle Spatial and Graph
Spatial DBMS infowith Oracle Spatial and Graph
Vector DBMS infosince Oracle 23
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1244.08
Rank#1  Overall
#1  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitekx.comazure.microsoft.com/­services/­data-explorerwww.oracle.com/­databasesphinxsearch.comvitess.io
Technical documentationcode.kx.comdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­databasesphinxsearch.com/­docsvitess.io/­docs
DeveloperKx Systems, a division of First Derivatives plcMicrosoftOracleSphinx Technologies Inc.The Linux Foundation, PlanetScale
Initial release2000 infokdb was released 2000, kdb+ in 20032019198020012013
Current release3.6, May 2018cloud service with continuous releases23c, September 20233.5.1, February 202315.0.2, December 2022
License infoCommercial or Open Sourcecommercial infofree 32-bit versioncommercialcommercial inforestricted free version is availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageqC and C++C++Go
Server operating systemsLinux
OS X
Solaris
Windows
hostedAIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Docker
Linux
macOS
Data schemeyesFixed schema with schema-less datatypes (dynamic)yes infoSchemaless in JSON and XML columnsyesyes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesnoyes
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.yesyesyes
Secondary indexesyes infotable attribute 'grouped'all fields are automatically indexedyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query language (q)Kusto Query Language (KQL), SQL subsetyes infowith proprietary extensionsSQL-like query language (SphinxQL)yes infowith proprietary extensions
APIs and other access methodsHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary protocolADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsYes, possible languages: KQL, Python, RPL/SQL infoalso stored procedures in Java possiblenoyes infoproprietary syntax
Triggersyes infowith viewsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoImplicit feature of the cloud serviceSharding, horizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infosimilar paradigm used for internal processingSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infocan be realized in PL/SQLnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesnoyesnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoisolation level can be parameterizednoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoVersion 12c introduced the new option 'Oracle Database In-Memory'yes
User concepts infoAccess controlrights management via user accountsAzure Active Directory Authenticationfine grained access rights according to SQL-standardnoUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
KdbMicrosoft Azure Data ExplorerOracleSphinxVitess
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...
» more
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
» more

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More resources
KdbMicrosoft Azure Data ExplorerOracleSphinxVitess
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