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DBMS > GeoMesa vs. LeanXcale vs. Microsoft Azure AI Search vs. Pinecone

System Properties Comparison GeoMesa vs. LeanXcale vs. Microsoft Azure AI Search vs. Pinecone

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonPinecone  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesSearch-as-a-service for web and mobile app developmentA managed, cloud-native vector database
Primary database modelSpatial DBMSKey-value store
Relational DBMS
Search engineVector DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score3.23
Rank#92  Overall
#2  Vector DBMS
Websitewww.geomesa.orgwww.leanxcale.comazure.microsoft.com/­en-us/­services/­searchwww.pinecone.io
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmllearn.microsoft.com/­en-us/­azure/­searchdocs.pinecone.io/­docs/­overview
DeveloperCCRi and othersLeanXcaleMicrosoftPinecone Systems, Inc
Initial release2014201520152019
Current release5.0.0, May 2024V1
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScala
Server operating systemshostedhosted
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesString, Number, Boolean
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.nonono
Secondary indexesyesyes
SQL infoSupport of SQLnoyes infothrough Apache Derbynono
APIs and other access methodsJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
RESTful HTTP APIRESTful HTTP API
Supported programming languagesC
Java
Scala
C#
Java
JavaScript
Python
Python
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layeryes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
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 layeryesnono
User concepts infoAccess controlyes infodepending on the DBMS used for storageyes infousing Azure authentication

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More resources
GeoMesaLeanXcaleMicrosoft Azure AI SearchPinecone
DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Vector databases
2 June 2023, Matthias Gelbmann

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