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DBMS > Blueflood vs. Microsoft Azure Data Explorer vs. Sphinx vs. Tigris

System Properties Comparison Blueflood vs. Microsoft Azure Data Explorer vs. Sphinx vs. Tigris

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Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparisonTigris  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraFully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databasesA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelTime Series DBMSRelational DBMS infocolumn orientedSearch engineDocument store
Key-value store
Search engine
Time Series DBMS
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
Score5.95
Rank#55  Overall
#5  Search engines
Score0.09
Rank#363  Overall
#49  Document stores
#54  Key-value stores
#22  Search engines
#38  Time Series DBMS
Websiteblueflood.ioazure.microsoft.com/­services/­data-explorersphinxsearch.comwww.tigrisdata.com
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docswww.tigrisdata.com/­docs
DeveloperRackspaceMicrosoftSphinx Technologies Inc.Tigris Data, Inc.
Initial release2013201920012022
Current releasecloud service with continuous releases3.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemsLinux
OS X
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemepredefined schemeFixed schema with schema-less datatypes (dynamic)yesyes
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-typesnoyes
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 indexedyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)no
APIs and other access methodsHTTP RESTMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocolCLI Client
gRPC
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Go
Java
JavaScript (Node.js)
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 infoPartitioning is done manually, search queries against distributed index is supportedSharding
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.noneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
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 integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes, using FoundationDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoAzure Active Directory AuthenticationnoAccess rights for users and roles

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More resources
BluefloodMicrosoft Azure Data ExplorerSphinxTigris
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