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DBMS > Blueflood vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage vs. Sphinx

System Properties Comparison Blueflood vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage vs. Sphinx

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Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraFully managed big data interactive analytics platformA Wide Column Store for rapid development using massive semi-structured datasetsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSRelational DBMS infocolumn orientedWide column storeSearch 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#346  Overall
#33  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score5.95
Rank#55  Overall
#5  Search engines
Websiteblueflood.ioazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­services/­storage/­tablessphinxsearch.com
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docs
DeveloperRackspaceMicrosoftMicrosoftSphinx Technologies Inc.
Initial release2013201920122001
Current releasecloud service with continuous releases3.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsLinux
OS X
hostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemepredefined schemeFixed schema with schema-less datatypes (dynamic)schema-freeyes
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-typesyesno
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.noyesno
Secondary indexesnoall fields are automatically indexednoyes infofull-text index on all search fields
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetnoSQL-like query language (SphinxQL)
APIs and other access methodsHTTP RESTMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIProprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Rnono
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraSharding infoImplicit feature of the cloud serviceSharding 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 nodesselectable replication factor infobased on Cassandrayes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingno
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.nonono
User concepts infoAccess controlnoAzure Active Directory AuthenticationAccess rights based on private key authentication or shared access signaturesno

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BluefloodMicrosoft Azure Data ExplorerMicrosoft Azure Table StorageSphinx
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