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DBMS > Hazelcast vs. Kinetica vs. Microsoft Azure Data Explorer vs. Sqrrl

System Properties Comparison Hazelcast vs. Kinetica vs. Microsoft Azure Data Explorer vs. Sqrrl

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionA widely adopted in-memory data gridGPU-accelerated database for real-time analysis of large and streaming datasetsFully managed big data interactive analytics platformAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelKey-value storeRelational DBMSRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.36
Rank#45  Overall
#5  Key-value stores
Score0.57
Rank#198  Overall
#96  Relational DBMS
Score2.33
Rank#104  Overall
#50  Relational DBMS
Websitehazelcast.comwww.kinetica.comazure.microsoft.com/­services/­data-explorersqrrl.com
Technical documentationhazelcast.org/­documentationwww.kinetica.com/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperHazelcastKineticaMicrosoftAmazon infooriginally Sqrrl Data, Inc.
Initial release2008201220192012
Current release3.12.2, August 20196.0
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++Java
Server operating systemsAll OS with a Java VMLinuxhostedLinux
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesuser defined functionsYes. Languages: KQL, Python, Rno
Triggersyes infoEventsyes infotriggers when inserted values for one or more columns fall within a specified rangeTable-level update policy rules can be used to automatically run a query and ingest its results when data is ingested into another table.no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding infomaking use of Hadoop
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.selectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednonoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlRole-based access controlAccess rights for users and roles on table levelAzure Active Directory AuthenticationCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)
More information provided by the system vendor
HazelcastKineticaMicrosoft Azure Data ExplorerSqrrl
Specific characteristicsHazelcast is an in-memory computing platform that runs applications with extremely...
» more
Competitive advantagesHazelcast has an optimized, multi-threaded architecture that enables the highest...
» more
Typical application scenariosHazelcast powers many types of large-scale, data processing applications. A sample...
» more
Key customersHazelcast customers include 50 of the world’s largest financial services companies,...
» more
Licensing and pricing modelsHazelcast provides both open source and commercial software. The open source offering...
» more

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HazelcastKineticaMicrosoft Azure Data ExplorerSqrrl
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