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DBMS > GeoMesa vs. InfinityDB vs. Microsoft Azure Data Explorer vs. OpenMLDB

System Properties Comparison GeoMesa vs. InfinityDB vs. Microsoft Azure Data Explorer vs. OpenMLDB

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonInfinityDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOpenMLDB  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.A Java embedded Key-Value Store which extends the Java Map interfaceFully managed big data interactive analytics platformAn open-source machine learning database that provides a feature platform for training and inference
Primary database modelSpatial DBMSKey-value storeRelational 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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score0.08
Rank#365  Overall
#55  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.10
Rank#359  Overall
#36  Time Series DBMS
Websitewww.geomesa.orgboilerbay.comazure.microsoft.com/­services/­data-exploreropenmldb.ai
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmlboilerbay.com/­infinitydb/­manualdocs.microsoft.com/­en-us/­azure/­data-exploreropenmldb.ai/­docs/­zh/­main
DeveloperCCRi and othersBoiler Bay Inc.Microsoft4 Paradigm Inc.
Initial release2014200220192020
Current release5.0.0, May 20244.0cloud service with continuous releases2024-2 February 2024
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaJavaC++, Java, Scala
Server operating systemsAll OS with a Java VMhostedLinux
Data schemeyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeFixed schema with schema-less datatypes (dynamic)Fixed schema
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes 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.nonoyesno
Secondary indexesyesno infomanual creation possible, using inversions based on multi-value capabilityall fields are automatically indexedyes
SQL infoSupport of SQLnonoKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
SQLAlchemy
Supported programming languagesJava.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Go
Java
Python
Scala
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Rno
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layernoneSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layernoneyes 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-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate Consistency infoREAD-COMMITTED or SERIALIZEDEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilitynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoOptimistic locking for transactions; no isolation for bulk loadsnono
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 layernonoyes
User concepts infoAccess controlyes infodepending on the DBMS used for storagenoAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
GeoMesaInfinityDBMicrosoft Azure Data ExplorerOpenMLDB
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