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DBMS > Ehcache vs. GeoSpock vs. Spark SQL

System Properties Comparison Ehcache vs. GeoSpock vs. Spark SQL

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonGeoSpock  Xexclude from comparisonSpark SQL  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionA widely adopted Java cache with tiered storage optionsSpatial and temporal data processing engine for extreme data scaleSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.89
Rank#67  Overall
#8  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.ehcache.orggeospock.comspark.apache.org/­sql
Technical documentationwww.ehcache.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperTerracotta Inc, owned by Software AGGeoSpockApache Software Foundation
Initial release20092014
Current release3.10.0, March 20222.0, September 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, JavascriptScala
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Windows
Data schemeschema-freeyesyes
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 indexesnotemporal, categoricalno
SQL infoSupport of SQLnoANSI SQL for query only (using Presto)SQL-like DML and DDL statements
APIs and other access methodsJCacheJDBCJDBC
ODBC
Supported programming languagesJavaJava
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersyes infoCache Event Listenersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerAutomatic shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Servernone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourcenono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlnoAccess rights for users can be defined per tableno

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More resources
EhcacheGeoSpockSpark SQL
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