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DBMS > Hazelcast vs. Microsoft Azure Data Explorer vs. SwayDB

System Properties Comparison Hazelcast vs. Microsoft Azure Data Explorer vs. SwayDB

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionA widely adopted in-memory data gridFully managed big data interactive analytics platformAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelKey-value storeRelational DBMS infocolumn orientedKey-value store
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
Score5.97
Rank#57  Overall
#6  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitehazelcast.comazure.microsoft.com/­services/­data-explorerswaydb.simer.au
Technical documentationhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperHazelcastMicrosoftSimer Plaha
Initial release200820192018
Current release5.3.6, November 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScala
Server operating systemsAll OS with a Java VMhosted
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)schema-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-typesno
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
Secondary indexesyesall fields are automatically indexedno
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful 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
Java
Kotlin
Scala
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, Rno
Triggersyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenone
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.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlRole-based access controlAzure Active Directory Authenticationno

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More resources
HazelcastMicrosoft Azure Data ExplorerSwayDB
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