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DBMS > GeoMesa vs. HEAVY.AI vs. Rockset vs. Yaacomo

System Properties Comparison GeoMesa vs. HEAVY.AI vs. Rockset vs. Yaacomo

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonRockset  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA scalable, reliable search and analytics service in the cloud, built on RocksDBOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelSpatial DBMSRelational DBMSDocument storeRelational DBMS
Secondary database modelsSpatial DBMSRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Websitewww.geomesa.orggithub.com/­heavyai/­heavydb
www.heavy.ai
rockset.comyaacomo.com
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.heavy.aidocs.rockset.com
DeveloperCCRi and othersHEAVY.AI, Inc.RocksetQ2WEB GmbH
Initial release2014201620192009
Current release4.0.5, February 20245.10, January 2022
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache Version 2; enterprise edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC++ and CUDAC++
Server operating systemsLinuxhostedAndroid
Linux
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesdynamic 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.nonono infoingestion from XML files supportedno
Secondary indexesyesnoall fields are automatically indexedyes
SQL infoSupport of SQLnoyesRead-only SQL queries, including JOINsyes
APIs and other access methodsJDBC
ODBC
Thrift
Vega
HTTP RESTJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonono
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerSharding infoRound robinAutomatic shardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerMulti-source replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
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 layeryesyes
User concepts infoAccess controlyes infodepending on the DBMS used for storagefine grained access rights according to SQL-standardAccess rights for users and organizations can be defined via Rockset consolefine grained access rights according to SQL-standard

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More resources
GeoMesaHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022RocksetYaacomo
DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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