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DBMS > GeoMesa vs. Microsoft Azure Data Explorer vs. Quasardb

System Properties Comparison GeoMesa vs. Microsoft Azure Data Explorer vs. Quasardb

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Fully managed big data interactive analytics platformDistributed, high-performance timeseries database
Primary database modelSpatial DBMSRelational DBMS infocolumn orientedTime Series DBMS
Secondary database modelsDocument 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
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitewww.geomesa.orgazure.microsoft.com/­services/­data-explorerquasar.ai
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdoc.quasar.ai/­master
DeveloperCCRi and othersMicrosoftquasardb
Initial release201420192009
Current release4.0.5, February 2024cloud service with continuous releases3.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
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 languageScalaC++
Server operating systemshostedBSD
Linux
OS X
Windows
Data schemeyesFixed 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-typesyes infointeger and binary
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.noyesno
Secondary indexesyesall fields are automatically indexedyes infowith tags
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetSQL-like query language
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Rno
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerSharding infoImplicit feature of the cloud serviceSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layeryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.depending on storage layernoyes infoTransient mode
User concepts infoAccess controlyes infodepending on the DBMS used for storageAzure Active Directory AuthenticationCryptographically strong user authentication and audit trail

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More resources
GeoMesaMicrosoft Azure Data ExplorerQuasardb
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