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DBMS > Ehcache vs. FatDB vs. Spark SQL vs. Warp 10

System Properties Comparison Ehcache vs. FatDB vs. Spark SQL vs. Warp 10

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonWarp 10  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.Spark SQL is a component on top of 'Spark Core' for structured data processingTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelKey-value storeDocument store
Key-value store
Relational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.64
Rank#68  Overall
#8  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websitewww.ehcache.orgspark.apache.org/­sqlwww.warp10.io
Technical documentationwww.ehcache.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.warp10.io/­content/­02_Getting_started
DeveloperTerracotta Inc, owned by Software AGFatCloudApache Software FoundationSenX
Initial release2009201220142015
Current release3.10.0, March 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache 2.0Open Source infoApache License 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#ScalaJava
Server operating systemsAll OS with a Java VMWindowsLinux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesschema-free
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-like DML and DDL statementsno
APIs and other access methodsJCache.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
HTTP API
Jupyter
WebSocket
Supported programming languagesJavaC#Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsnoyes infoWarpScript
Triggersyes infoCache Event Listenersyes infovia applicationsnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingyes, utilizing Spark CoreSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Serverselectable replication factornoneselectable replication factor infobased on HBase
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
Immediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourcenonono
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.yesnoyes
User concepts infoAccess controlnono infoCan implement custom security layer via applicationsnoMandatory use of cryptographic tokens, containing fine-grained authorizations

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EhcacheFatDBSpark SQLWarp 10
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