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

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

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRockset  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 managed big data interactive analytics platformA scalable, reliable search and analytics service in the cloud, built on RocksDBAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelKey-value storeRelational DBMSDocument storeDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store infoJSON support with IMDG 3.12Relational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.36
Rank#45  Overall
#5  Key-value stores
Score2.33
Rank#104  Overall
#50  Relational DBMS
Score0.39
Rank#221  Overall
#31  Document stores
Websitehazelcast.comazure.microsoft.com/­services/­data-explorerrockset.comsqrrl.com
Technical documentationhazelcast.org/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.rockset.com/­overview
DeveloperHazelcastMicrosoftRocksetAmazon infooriginally Sqrrl Data, Inc.
Initial release2008201920192012
Current release3.12.2, August 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java
Server operating systemsAll OS with a Java VMhostedhostedLinux
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesdynamic typingyes
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 strategyyesno infoingestion from XML files supported
Secondary indexesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetRead-only SQL queries, including JOINsno
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP RESTAccumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Java
JavaScript (Node.js)
PowerShell
Python
R
Go
Java
JavaScript (Node.js)
Python
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 ServicesYes. Languages: KQL, Python, Rnono
Triggersyes infoEventsTable-level update policy rules can be used to automatically run a query and ingest its results when data is ingested into another table.nono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceAutomatic shardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesselectable 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 AlgorithmEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynononono
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.yesno
User concepts infoAccess controlRole-based access controlAzure Active Directory AuthenticationAccess rights for users and organizations can be defined via Rockset consoleCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)
More information provided by the system vendor
HazelcastMicrosoft Azure Data ExplorerRocksetSqrrl
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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HazelcastMicrosoft Azure Data ExplorerRocksetSqrrl
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