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

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

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonFatDB  Xexclude from comparisongStore  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.A native Graph DBMS to store and maintain very large RDF datasets.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeDocument store
Key-value store
Graph DBMS
RDF store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.64
Rank#68  Overall
#8  Key-value stores
Score0.14
Rank#342  Overall
#34  Graph DBMS
#16  RDF stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.ehcache.orgen.gstore.cnspark.apache.org/­sql
Technical documentationwww.ehcache.org/­documentationen.gstore.cn/­#/­enDocsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperTerracotta Inc, owned by Software AGFatCloudApache Software Foundation
Initial release2009201220162014
Current release3.10.0, March 20221.2, November 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#C++Scala
Server operating systemsAll OS with a Java VMWindowsLinuxLinux
OS X
Windows
Data schemeschema-freeschema-freeschema-free and OWL/RDFS-schema supportyes
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 indexesnoyesno
SQL infoSupport of SQLnono infoVia inetgration in SQL ServernoSQL-like DML and DDL statements
APIs and other access methodsJCache.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
HTTP API
SPARQL 1.1
JDBC
ODBC
Supported programming languagesJavaC#C++
Java
JavaScript (Node.js)
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsyesno
Triggersyes infoCache Event Listenersyes infovia applicationsno
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Serverselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
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 resourcenoyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlnono infoCan implement custom security layer via applicationsUsers, roles and permissions, Role-Based Access Control (RBAC) supportedno

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More resources
EhcacheFatDBgStoreSpark SQL
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