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DBMS > Microsoft Azure Data Explorer vs. Rockset vs. Spark SQL vs. Sphinx

System Properties Comparison Microsoft Azure Data Explorer vs. Rockset vs. Spark SQL vs. Sphinx

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformA scalable, reliable search and analytics service in the cloud, built on RocksDBSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMS infocolumn orientedDocument storeRelational DBMSSearch engine
Secondary database modelsDocument 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
Relational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteazure.microsoft.com/­services/­data-explorerrockset.comspark.apache.org/­sqlsphinxsearch.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperMicrosoftRocksetApache Software FoundationSphinx Technologies Inc.
Initial release2019201920142001
Current releasecloud service with continuous releases3.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++
Server operating systemshostedhostedLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFixed schema with schema-less datatypes (dynamic)schema-freeyesyes
Typing infopredefined data types such as float or dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesdynamic typingyesno
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.yesno infoingestion from XML files supportedno
Secondary indexesall fields are automatically indexedall fields are automatically indexednoyes infofull-text index on all search fields
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetRead-only SQL queries, including JOINsSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP RESTJDBC
ODBC
Proprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Rnonono
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceAutomatic shardingyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAzure Active Directory AuthenticationAccess rights for users and organizations can be defined via Rockset consolenono

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Microsoft Azure Data ExplorerRocksetSpark SQLSphinx
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