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

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

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionA widely adopted in-memory data gridRDBMS for high security requirementsFully managed big data interactive analytics platform
Primary database modelKey-value storeRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document 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
Score8.45
Rank#48  Overall
#6  Key-value stores
Score0.01
Rank#334  Overall
#137  Relational DBMS
Score3.58
Rank#84  Overall
#42  Relational DBMS
Websitehazelcast.comlinter.ru/­enazure.microsoft.com/­services/­data-explorer
Technical documentationhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperHazelcastrelex.ru/­enMicrosoft
Initial release200819902019
Current release4.0, February 2020cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++
Server operating systemsAll OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hosted
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)
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-types
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 indexed
SQL infoSupport of SQLSQL-like query languageyesKusto Query Language (KQL), SQL subset
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
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
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesyes infoproprietary syntax with the possibility to convert from PL/SQLYes, possible languages: KQL, Python, R
Triggersyes infoEventsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapMaster-slave replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
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 integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
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 Authentication
More information provided by the system vendor
HazelcastLinterMicrosoft Azure Data Explorer
Specific characteristicsHazelcast is an in-memory computing platform that runs applications with extremely...
» more
Azure Data Explorer is a fast and highly scalable data exploration service for log...
» more
Competitive advantagesHazelcast has an optimized, multi-threaded architecture that enables the highest...
» more
Kusto Query Language (innovative query language, optimized for high performance data...
» more
Typical application scenariosHazelcast powers many types of large-scale, data processing applications. A sample...
» more
IoT applications IoT devices generate billions of sensor readings. Normalizing and...
» more
Key customersHazelcast customers include 50 of the world’s largest financial services companies,...
» more
Microsoft, 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
Licensing and pricing modelsHazelcast provides both open source and commercial software. The open source offering...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
HazelcastLinterMicrosoft Azure Data Explorer
Recent citations in the news

Global In-Memory Data Grid Market 2020 – Impact of COVID-19, Future Growth Analysis and Challenges | Oracle, IBM, Hazelcast, Scale Out Software, Tibco Software
2 July 2020, Bandera County Courier

Global In-Memory Data Grid Market 2020 Top Key Players | Oracle, IBM, Hazelcast, Scale Out Software, Tibco Software
2 July 2020, Bandera County Courier

Hazelcast raises $50 million to deliver speedy in-memory compute services
12 February 2020, VentureBeat

COVID-19 Update: Global In-Memory Data Grids Market is Expected to Grow at a Healthy CAGR with Top players: IBM, Software AG, Hazelcast, Pivotal, GigaSpaces Technologies, etc. | InForGrowth
2 July 2020, Jewish Life News

Latest News 2020: In-Memory Data Grid Market by Coronavirus-COVID19 Impact Analysis With Top Manufacturers Analysis | Top Players: Oracle, IBM, Hazelcast, Scale Out Software, Tibco Software, etc. | InForGrowth
16 June 2020, Jewish Life News

provided by Google News

Azure Updates: Covid-19; Teams; SAP; VMs; IoT Hub
23 June 2020, MSDynamicsWorld.com

IS Engineering Lead
22 June 2020, OilVoice

Zoomd Takes Another Step Towards Becoming an Industry Leader After Adopting Microsoft's Azure Data Explorer
4 December 2019, PRNewswire

Fastly, Microsoft partner on real-time analytics with Azure Data Explorer
29 January 2019, ZDNet

How to use Azure Data Explorer for large-scale data analysis
12 February 2019, InfoWorld

provided by Google News

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