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DBMS > Ehcache vs. FatDB vs. FeatureBase vs. Spark SQL

System Properties Comparison Ehcache vs. FatDB vs. FeatureBase vs. Spark SQL

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonFatDB  Xexclude from comparisonFeatureBase  Xexclude from comparisonSpark SQL  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA widely adopted Java cache with tiered storage optionsA .NET NoSQL DBMS that can integrate with and extend SQL Server.Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeDocument store
Key-value store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.64
Rank#68  Overall
#8  Key-value stores
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.ehcache.orgwww.featurebase.comspark.apache.org/­sql
Technical documentationwww.ehcache.org/­documentationdocs.featurebase.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperTerracotta Inc, owned by Software AGFatCloudMolecula and Pilosa Open Source ContributorsApache Software Foundation
Initial release2009201220172014
Current release3.10.0, March 20222022, May 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC#GoScala
Server operating systemsAll OS with a Java VMWindowsLinux
macOS
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyes
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.nonono
Secondary indexesnoyesnono
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSQL queriesSQL-like DML and DDL statements
APIs and other access methodsJCache.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC
JDBC
Kafka Connector
ODBC
JDBC
ODBC
Supported programming languagesJavaC#Java
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsno
Triggersyes infoCache Event Listenersyes infovia applicationsnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Serverselectable replication factoryesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourcenoyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyes, using Linux fsyncyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlnono infoCan implement custom security layer via applicationsno

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More resources
EhcacheFatDBFeatureBaseSpark SQL
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