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DBMS > Hazelcast vs. Microsoft Azure Data Explorer vs. Quasardb vs. Sqrrl vs. Yanza

System Properties Comparison Hazelcast vs. Microsoft Azure Data Explorer vs. Quasardb vs. Sqrrl vs. Yanza

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonQuasardb  Xexclude from comparisonSqrrl  Xexclude from comparisonYanza  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.Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA widely adopted in-memory data gridFully managed big data interactive analytics platformDistributed, high-performance timeseries databaseAdaptable, secure NoSQL built on Apache AccumuloTime Series DBMS for IoT Applications
Primary database modelKey-value storeRelational DBMS infocolumn orientedTime Series DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Time Series DBMS
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)
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
Score7.66
Rank#54  Overall
#5  Key-value stores
Score5.82
Rank#65  Overall
#37  Relational DBMS
Score0.19
Rank#330  Overall
#30  Time Series DBMS
Websitehazelcast.comazure.microsoft.com/­services/­data-explorerquasar.aisqrrl.comyanza.com
Technical documentationhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdoc.quasar.ai/­master
DeveloperHazelcastMicrosoftquasardbAmazon infooriginally Sqrrl Data, Inc.Yanza
Initial release20082019200920122015
Current release5.3.6, November 2023cloud service with continuous releases3.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensescommercialcommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenoyesnonono infobut mainly used as a service provided by Yanza
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 VMhostedBSD
Linux
OS X
Windows
LinuxWindows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)schema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infointeger and binaryyesno
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 strategyyesnono
Secondary indexesyesall fields are automatically indexedyes infowith tagsyesno
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetSQL-like query languagenono
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP APIAccumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
HTTP API
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
any language that supports HTTP calls
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, Rnonono
Triggersyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infoconsistent hashingSharding infomaking use of Hadoopnone
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.Source-replica replication with selectable replication factorselectable replication factor infomaking use of Hadoopnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integrationyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednoACIDAtomic updates per row, document, or graph entityno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoTransient mode
User concepts infoAccess controlRole-based access controlAzure Active Directory AuthenticationCryptographically strong user authentication and audit trailCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)no

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More resources
HazelcastMicrosoft Azure Data ExplorerQuasardbSqrrlYanza
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