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DBMS > Datomic vs. Microsoft Azure Data Explorer vs. Sphinx

System Properties Comparison Datomic vs. Microsoft Azure Data Explorer vs. Sphinx

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMS infocolumn orientedSearch 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)
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
Score2.83
Rank#101  Overall
#49  Relational DBMS
Score3.71
Rank#83  Overall
#42  Relational DBMS
Score6.47
Rank#59  Overall
#7  Search engines
Websitewww.datomic.comazure.microsoft.com/­services/­data-explorersphinxsearch.com
Technical documentationdocs.datomic.comdocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docs
DeveloperCognitectMicrosoftSphinx Technologies Inc.
Initial release201220192001
Current release0.9.5951, July 2019cloud service with continuous releases3.2.1, January 2020
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++
Server operating systemsAll OS with a Java VMhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)yes
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-typesno
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.noyes
Secondary indexesyesall fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocol
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infoTransaction FunctionsYes, possible languages: KQL, Python, Rno
TriggersBy using transaction functionsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes 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.yes inforecommended only for testing and developmentno
User concepts infoAccess controlnoAzure Active Directory Authenticationno
More information provided by the system vendor
DatomicMicrosoft Azure Data ExplorerSphinx
Specific characteristicsAzure Data Explorer is a fast and highly scalable data exploration service for log...
» more
Competitive advantagesKusto Query Language (innovative query language, optimized for high performance data...
» more
Typical application scenariosIoT applications IoT devices generate billions of sensor readings. Normalizing and...
» more
Key customersMicrosoft, DocuSign, Taboola, Bosch, Siemens Healthineers, Bühler, Ecolab, Zoomd
» more
Market metricsAzure Data Explorer is the data service for Azure Monitor, Azure Time Series Insights,...
» more

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DatomicMicrosoft Azure Data ExplorerSphinx
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