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

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

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Editorial information provided by DB-Engines
NameEventStoreDB  Xexclude from comparisonGeoMesa  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionIndustrial-strength, open-source database solution built from the ground up for event sourcing.GeoMesa 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 RDBMS
Primary database modelEvent StoreSpatial DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.10
Rank#179  Overall
#1  Event Stores
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitewww.eventstore.comwww.geomesa.orgspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdevelopers.eventstore.comwww.geomesa.org/­documentation/­stable/­user/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperEvent Store LimitedCCRi and othersApache Software FoundationTransaction Software GmbH
Initial release2012201420141987
Current release21.2, February 20214.0.5, February 20243.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen SourceOpen Source infoApache License 2.0Open Source infoApache 2.0commercial infofree development license
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++
Server operating systemsLinux
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
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 indexesyesnoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes
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
Server-side scripts infoStored proceduresnonoyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layeryes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layernoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
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 datanonoyes
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.depending on storage layernono
User concepts infoAccess controlyes infodepending on the DBMS used for storagenofine grained access rights according to SQL-standard

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More resources
EventStoreDBGeoMesaSpark SQLTransbase
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