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DBMS > Ehcache vs. EJDB vs. FatDB vs. Google Cloud Firestore vs. Spark SQL

System Properties Comparison Ehcache vs. EJDB vs. FatDB vs. Google Cloud Firestore vs. Spark SQL

Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonEJDB  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Firestore  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 optionsEmbeddable document-store database library with JSON representation of queries (in MongoDB style)A .NET NoSQL DBMS that can integrate with and extend SQL Server.Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeDocument storeDocument store
Key-value store
Document storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.89
Rank#67  Overall
#8  Key-value stores
Score0.27
Rank#297  Overall
#44  Document stores
Score7.85
Rank#51  Overall
#8  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.ehcache.orggithub.com/­Softmotions/­ejdbfirebase.google.com/­products/­firestorespark.apache.org/­sql
Technical documentationwww.ehcache.org/­documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdfirebase.google.com/­docs/­firestorespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperTerracotta Inc, owned by Software AGSoftmotionsFatCloudGoogleApache Software Foundation
Initial release20092012201220172014
Current release3.10.0, March 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPLv2commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC#Scala
Server operating systemsAll OS with a Java VMserver-lessWindowshostedLinux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyesyesyes
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 indexesnonoyesyesno
SQL infoSupport of SQLnonono infoVia inetgration in SQL ServernoSQL-like DML and DDL statements
APIs and other access methodsJCachein-process shared library.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Supported programming languagesJavaActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infovia applicationsyes, Firebase Rules & Cloud Functionsno
Triggersyes infoCache Event Listenersnoyes infovia applicationsyes, with Cloud Functionsno
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServernoneShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Servernoneselectable replication factorMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesUsing Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourcenonoyesno
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlnonono infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.no

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More resources
EhcacheEJDBFatDBGoogle Cloud FirestoreSpark SQL
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