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DBMS > GeoMesa vs. IBM Db2 vs. Microsoft Azure Data Explorer vs. Solr vs. Trino

System Properties Comparison GeoMesa vs. IBM Db2 vs. Microsoft Azure Data Explorer vs. Solr vs. Trino

Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSolr  Xexclude from comparisonTrino  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Common in IBM host environments, 2 different versions for host and Windows/LinuxFully managed big data interactive analytics platformA widely used distributed, scalable search engine based on Apache LuceneFast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL
Primary database modelSpatial DBMSRelational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBRelational DBMS infocolumn orientedSearch engineRelational DBMS
Secondary database modelsDocument store
RDF store infoin Db2 LUW (Linux, Unix, Windows)
Spatial DBMS infowith Db2 Spatial Extender
Document 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
Spatial DBMSDocument store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score128.46
Rank#8  Overall
#5  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score5.00
Rank#66  Overall
#36  Relational DBMS
Websitewww.geomesa.orgwww.ibm.com/­products/­db2azure.microsoft.com/­services/­data-explorersolr.apache.orgtrino.io
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmlwww.ibm.com/­docs/­en/­db2docs.microsoft.com/­en-us/­azure/­data-explorersolr.apache.org/­resources.htmltrino.io/­broadcast
trino.io/­docs/­current
Social network pagesLinkedInTwitterYouTubeGitHub
DeveloperCCRi and othersIBMMicrosoftApache Software FoundationTrino Software Foundation
Initial release20141983 infohost version201920062012 info2020 rebranded from PrestoSQL
Current release4.0.5, February 202412.1, October 2016cloud service with continuous releases9.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercial infofree version is availablecommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.
Implementation languageScalaC and C++JavaJava
Server operating systemsAIX
HP-UX
Linux
Solaris
Windows
z/OS
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
macOS infofor devlopment
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes infoDynamic Fields enables on-the-fly addition of new fieldsyes
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 infosupports customizable data types and automatic typingyes
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.noyesyesno
Secondary indexesyesyesall fields are automatically indexedyes infoAll search fields are automatically indexeddepending on connected data-source
SQL infoSupport of SQLnoyesKusto Query Language (KQL), SQL subsetSolr Parallel SQL Interfaceyes
APIs and other access methodsADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
RESTful HTTP/JSON API
JDBC
RESTful HTTP API
Trino CLI
Supported programming languagesC
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Go
Java
JavaScript (Node.js)
Python
R
Ruby
Server-side scripts infoStored proceduresnoyesYes, possible languages: KQL, Python, RJava pluginsyes, depending on connected data-source
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerSharding infoonly with Windows/Unix/Linux VersionSharding infoImplicit feature of the cloud serviceShardingdepending on connected data-source
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layeryes infowith separate tools (MQ, InfoSphere)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesdepending on connected data-source
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerEventual Consistency
Immediate Consistency
Eventual Consistencydepending on connected data-source
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnooptimistic lockingdepending on connected data-source
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesdepending on connected data-source
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.depending on storage layernoyes
User concepts infoAccess controlyes infodepending on the DBMS used for storagefine grained access rights according to SQL-standardAzure Active Directory AuthenticationyesSQL standard access control
More information provided by the system vendor
GeoMesaIBM Db2 infoformerly named DB2 or IBM Database 2Microsoft Azure Data ExplorerSolrTrino
Specific characteristicsTrino is the fastest open source, massively parallel processing SQL query engine...
» more
Competitive advantagesHigh performance analtyics and data processing of very large data sets Powerful ANSI...
» more
Typical application scenariosPerformant analytics query engine for data warehouses, data lakes, and data lakehouses...
» more
Key customersTrino is widely adopted across the globe as freely-available open source software....
» more
Market metrics33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
» more
Licensing and pricing modelsTrino is an open source project and usage is therefore free. Commercial offerings...
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
GeoMesaIBM Db2 infoformerly named DB2 or IBM Database 2Microsoft Azure Data ExplorerSolrTrino
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