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

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

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonHBase  Xexclude from comparisonKdb  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionA widely adopted in-memory data gridWide-column store based on Apache Hadoop and on concepts of BigTableHigh performance Time Series DBMSRDBMS for high security requirementsFully managed big data interactive analytics platform
Primary database modelKey-value storeWide column storeTime Series DBMS
Vector DBMS
Relational DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument store infoJSON support with IMDG 3.12Relational DBMSSpatial 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
Score30.50
Rank#26  Overall
#2  Wide column stores
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitehazelcast.comhbase.apache.orgkx.comlinter.ruazure.microsoft.com/­services/­data-explorer
Technical documentationhazelcast.org/­imdg/­docshbase.apache.org/­book.htmlcode.kx.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperHazelcastApache Software Foundation infoApache top-level project, originally developed by PowersetKx Systems, a division of First Derivatives plcrelex.ruMicrosoft
Initial release200820082000 infokdb was released 2000, kdb+ in 200319902019
Current release5.3.6, November 20232.3.4, January 20213.6, May 2018cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache version 2commercial infofree 32-bit versioncommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaqC and C++
Server operating systemsAll OS with a Java VMLinux
Unix
Windows infousing Cygwin
Linux
OS X
Solaris
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hosted
Data schemeschema-freeschema-free, schema definition possibleyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyesyes 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 strategynoyesnoyes
Secondary indexesyesnoyes infotable attribute 'grouped'yesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenoSQL-like query language (q)yesKusto Query Language (KQL), SQL subset
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
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++
Groovy
Java
PHP
Python
Scala
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesyes infoCoprocessors in Javauser defined functionsyes infoproprietary syntax with the possibility to convert from PL/SQLYes, possible languages: KQL, Python, R
Triggersyes infoEventsyesyes infowith viewsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapMulti-source replication
Source-replica replication
Source-replica replicationSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno infosimilar paradigm used for internal processingnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedSingle row ACID (across millions of columns)noACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlRole-based access controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACrights management via user accountsfine grained access rights according to SQL-standardAzure Active Directory Authentication
More information provided by the system vendor
HazelcastHBaseKdbLinterMicrosoft Azure Data Explorer
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
HazelcastHBaseKdbLinterMicrosoft Azure Data Explorer
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