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DBMS > GeoMesa vs. Microsoft Azure AI Search vs. Microsoft Azure Data Explorer vs. Netezza

System Properties Comparison GeoMesa vs. Microsoft Azure AI Search vs. Microsoft Azure Data Explorer vs. Netezza

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Search-as-a-service for web and mobile app developmentFully managed big data interactive analytics platformData warehouse and analytics appliance part of IBM PureSystems
Primary database modelSpatial DBMSSearch engineRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsVector DBMSDocument 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
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websitewww.geomesa.orgazure.microsoft.com/­en-us/­services/­searchazure.microsoft.com/­services/­data-explorerwww.ibm.com/­products/­netezza
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmllearn.microsoft.com/­en-us/­azure/­searchdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperCCRi and othersMicrosoftMicrosoftIBM
Initial release2014201520192000
Current release5.0.0, May 2024V1cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercialcommercial
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 languageScala
Server operating systemshostedhostedLinux infoincluded in appliance
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyes 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.nonoyes
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLnonoKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsRESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
OLE DB
Supported programming languagesC#
Java
JavaScript
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Ryes
Triggersnonoyes 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 infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layeryes infoImplicit feature of the cloud serviceyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
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.depending on storage layernono
User concepts infoAccess controlyes infodepending on the DBMS used for storageyes infousing Azure authenticationAzure Active Directory AuthenticationUsers with fine-grained authorization concept

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More resources
GeoMesaMicrosoft Azure AI SearchMicrosoft Azure Data ExplorerNetezza infoAlso called PureData System for Analytics by IBM
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