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DBMS > GeoMesa vs. Microsoft Azure AI Search vs. Pinecone vs. Splice Machine

System Properties Comparison GeoMesa vs. Microsoft Azure AI Search vs. Pinecone vs. Splice Machine

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonPinecone  Xexclude from comparisonSplice Machine  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 developmentA managed, cloud-native vector databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelSpatial DBMSSearch engineVector DBMSRelational 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
Score5.52
Rank#59  Overall
#6  Search engines
Score3.23
Rank#92  Overall
#2  Vector DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.geomesa.orgazure.microsoft.com/­en-us/­services/­searchwww.pinecone.iosplicemachine.com
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmllearn.microsoft.com/­en-us/­azure/­searchdocs.pinecone.io/­docs/­overviewsplicemachine.com/­how-it-works
DeveloperCCRi and othersMicrosoftPinecone Systems, IncSplice Machine
Initial release2014201520192014
Current release5.0.0, May 2024V13.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercialOpen Source infoAGPL 3.0, commercial license available
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 languageScalaJava
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesString, Number, Booleanyes
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 indexesyesyesyes
SQL infoSupport of SQLnononoyes
APIs and other access methodsRESTful HTTP APIRESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Java
JavaScript
Python
PythonC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infoJava
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layeryes infoImplicit feature of the cloud serviceMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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 storageyes infousing Azure authenticationAccess rights for users, groups and roles according to SQL-standard

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More resources
GeoMesaMicrosoft Azure AI SearchPineconeSplice Machine
DB-Engines blog posts

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