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DBMS > GeoMesa vs. Spark SQL vs. Transbase vs. YTsaurus

System Properties Comparison GeoMesa vs. Spark SQL vs. Transbase vs. YTsaurus

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparisonYTsaurus  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Spark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMSYTsaurus is an open source platform for distributed storage and processing.
Primary database modelSpatial DBMSRelational DBMSRelational DBMSDocument store
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Score0.11
Rank#340  Overall
#45  Document stores
#50  Key-value stores
Websitewww.geomesa.orgspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.htmlytsaurus.tech
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.htmlytsaurus.tech/­docs/­en
DeveloperCCRi and othersApache Software FoundationTransaction Software GmbHYandex
Initial release2014201419872023
Current release4.0.5, February 20243.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache 2.0commercial infofree development licenseOpen Source infoApache License, Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaScalaC and C++C++
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Ubuntu
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononono
Secondary indexesyesnoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesYQL, an SQL-based language, is supported
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesJava
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
C++
Go
Java
JavaScript
Python
Server-side scripts infoStored proceduresnonoyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layeryes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layernoneSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesACID
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 layernono
User concepts infoAccess controlyes infodepending on the DBMS used for storagenofine grained access rights according to SQL-standardAccess Control Lists

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More resources
GeoMesaSpark SQLTransbaseYTsaurus
DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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