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DBMS > Badger vs. Hazelcast vs. Microsoft Azure Data Explorer vs. SiteWhere

System Properties Comparison Badger vs. Hazelcast vs. Microsoft Azure Data Explorer vs. SiteWhere

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSiteWhere  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A widely adopted in-memory data gridFully managed big data interactive analytics platformM2M integration platform for persisting/querying time series data
Primary database modelKey-value storeKey-value storeRelational DBMS infocolumn orientedTime 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
Score0.22
Rank#320  Overall
#47  Key-value stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websitegithub.com/­dgraph-io/­badgerhazelcast.comazure.microsoft.com/­services/­data-explorergithub.com/­sitewhere/­sitewhere
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorersitewhere1.sitewhere.io/­index.html
DeveloperDGraph LabsHazelcastMicrosoftSiteWhere
Initial release2017200820192010
Current release5.3.6, November 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoCommon Public Attribution License Version 1.0
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 languageGoJavaJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
All OS with a Java VMhostedLinux
OS X
Windows
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)predefined scheme
Typing infopredefined data types such as float or datenoyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.noyes infothe object must implement a serialization strategyyesno
Secondary indexesnoyesall fields are automatically indexedno
SQL infoSupport of SQLnoSQL-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
HTTP REST
Supported programming languagesGo.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, R
Triggersnoyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud serviceSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitednono
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.noyesnono
User concepts infoAccess controlnoRole-based access controlAzure Active Directory AuthenticationUsers with fine-grained authorization concept

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More resources
BadgerHazelcastMicrosoft Azure Data ExplorerSiteWhere
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