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DBMS > EsgynDB vs. GeoMesa vs. Spark SQL

System Properties Comparison EsgynDB vs. GeoMesa vs. Spark SQL

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGeoMesa  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGeoMesa 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 processing
Primary database modelRelational DBMSSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#320  Overall
#142  Relational DBMS
Score0.95
Rank#221  Overall
#4  Spatial DBMS
Score19.23
Rank#36  Overall
#22  Relational DBMS
Websitewww.esgyn.cnwww.geomesa.orgspark.apache.org/­sql
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynCCRi and othersApache Software Foundation
Initial release201520142014
Current release4.0.4, October 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache License 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaScalaScala
Server operating systemsLinuxLinux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesyesno
SQL infoSupport of SQLyesnoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetJava
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingdepending on storage layeryes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersdepending on storage layernone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistencydepending on storage layer
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nodepending on storage layerno
User concepts infoAccess controlfine grained access rights according to SQL-standardyes infodepending on the DBMS used for storageno

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More resources
EsgynDBGeoMesaSpark SQL
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