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DBMS > Ehcache vs. GridGain vs. Spark SQL vs. SWC-DB

System Properties Comparison Ehcache vs. GridGain vs. Spark SQL vs. SWC-DB

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonGridGain  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsGridGain is an in-memory computing platform, built on Apache IgniteSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMS
Primary database modelKey-value storeKey-value store
Relational DBMS
Relational DBMSWide column store
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
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websitewww.ehcache.orgwww.gridgain.comspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationwww.ehcache.org/­documentationwww.gridgain.com/­docs/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperTerracotta Inc, owned by Software AGGridGain Systems, Inc.Apache Software FoundationAlex Kashirin
Initial release2009200720142020
Current release3.10.0, March 2022GridGain 8.5.13.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .NetScalaC++
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeyesyesschema-free
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.noyesnono
Secondary indexesnoyesno
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsJCacheHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Proprietary protocol
Thrift
Supported programming languagesJavaC#
C++
Java
PHP
Python
Ruby
Scala
Java
Python
R
Scala
C++
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)nono
Triggersyes infoCache Event Listenersyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Serveryes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Immediate ConsistencyImmediate 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 resourceACIDno
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.yesyesnono
User concepts infoAccess controlnoSecurity Hooks for custom implementationsno

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EhcacheGridGainSpark SQLSWC-DB infoSuper Wide Column Database
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