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DBMS > Hazelcast vs. Linter vs. Microsoft Azure Data Explorer vs. Sphinx

System Properties Comparison Hazelcast vs. Linter vs. Microsoft Azure Data Explorer vs. Sphinx

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA widely adopted in-memory data gridRDBMS for high security requirementsFully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value storeRelational DBMSRelational DBMS infocolumn orientedSearch engine
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial 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
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitehazelcast.comlinter.ruazure.microsoft.com/­services/­data-explorersphinxsearch.com
Technical documentationhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docs
DeveloperHazelcastrelex.ruMicrosoftSphinx Technologies Inc.
Initial release2008199020192001
Current release5.3.6, November 2023cloud service with continuous releases3.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C++
Server operating systemsAll OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyes 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.yes infothe object must implement a serialization strategynoyes
Secondary indexesyesyesall fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageyesKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocol
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.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 infoEvent Listeners, Executor Servicesyes infoproprietary syntax with the possibility to convert from PL/SQLYes, possible languages: KQL, Python, Rno
Triggersyes infoEventsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding 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 nodesyes infoReplicated MapSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedACIDnono
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.yesno
User concepts infoAccess controlRole-based access controlfine grained access rights according to SQL-standardAzure Active Directory Authenticationno

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More resources
HazelcastLinterMicrosoft Azure Data ExplorerSphinx
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