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DBMS > Kdb vs. Microsoft Azure Data Explorer vs. Speedb vs. Sphinx vs. Splice Machine

System Properties Comparison Kdb vs. Microsoft Azure Data Explorer vs. Speedb vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameKdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpeedb  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHigh performance Time Series DBMSFully managed big data interactive analytics platformAn embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDBOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMS
Vector DBMS
Relational DBMS infocolumn orientedKey-value storeSearch 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
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
Score0.26
Rank#310  Overall
#45  Key-value stores
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitekx.comazure.microsoft.com/­services/­data-explorerwww.speedb.iosphinxsearch.comsplicemachine.com
Technical documentationcode.kx.comdocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperKx Systems, a division of First Derivatives plcMicrosoftSpeedbSphinx Technologies Inc.Splice Machine
Initial release2000 infokdb was released 2000, kdb+ in 20032019202020012014
Current release3.6, May 2018cloud service with continuous releases3.5.1, February 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infofree 32-bit versioncommercialOpen Source infoApache Version 2.0; commercial license availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license 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++C++Java
Server operating systemsLinux
OS X
Solaris
Windows
hostedLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)schema-freeyesyes
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-typesnonoyes
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.yesyesno
Secondary indexesyes infotable attribute 'grouped'all fields are automatically indexednoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query language (q)Kusto Query Language (KQL), SQL subsetnoSQL-like query language (SphinxQL)yes
APIs and other access methodsHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocolJDBC
Native Spark Datasource
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++
Go
Java
Perl
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsYes, possible languages: KQL, Python, Rnonoyes infoJava
Triggersyes infowith viewsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoImplicit feature of the cloud servicehorizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
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.yesnoneMulti-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-sparknonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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.yesnoyesyes
User concepts infoAccess controlrights management via user accountsAzure Active Directory AuthenticationnonoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
KdbMicrosoft Azure Data ExplorerSpeedbSphinxSplice Machine
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Speedb is an embedded key-value storage engine for versatile use cases. It was designed...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Speedb Open-source rebases on RocksDB's latest versions, with enhanced capabilities...
» 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
Open source - Speedb OSS is released under an Apache license and can be found on...
» more

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More resources
KdbMicrosoft Azure Data ExplorerSpeedbSphinxSplice Machine
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