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DBMS > Hazelcast vs. Kinetica vs. Microsoft Azure Table Storage vs. Sqrrl

System Properties Comparison Hazelcast vs. Kinetica vs. Microsoft Azure Table Storage vs. Sqrrl

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Table Storage  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 gridFully vectorized database across both GPUs and CPUsA Wide Column Store for rapid development using massive semi-structured datasetsAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelKey-value storeRelational DBMSWide column storeDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.87
Rank#55  Overall
#6  Key-value stores
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score4.92
Rank#73  Overall
#6  Wide column stores
Websitehazelcast.comwww.kinetica.comazure.microsoft.com/­en-us/­services/­storage/­tablessqrrl.com
Technical documentationhazelcast.org/­imdg/­docsdocs.kinetica.com
DeveloperHazelcastKineticaMicrosoftAmazon infooriginally Sqrrl Data, Inc.
Initial release2008201220122012
Current release5.3.6, November 20237.1, August 2021
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

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Implementation languageJavaC, C++Java
Server operating systemsAll OS with a Java VMLinuxhostedLinux
Data schemeschema-freeyesschema-freeschema-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 strategynono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsnono
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIAccumulo 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
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
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 functionsnono
Triggersyes infoEventsyes infotriggers when inserted values for one or more columns fall within a specified rangenono
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 MapSource-replica 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 configurationImmediate ConsistencyImmediate 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 commitednooptimistic lockingAtomic 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 levelAccess rights based on private key authentication or shared access signaturesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
HazelcastKineticaMicrosoft Azure Table StorageSqrrl
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