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

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

Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonOrientDB  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.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.Multi-model DBMS (Document, Graph, Key/Value)Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeDocument store
Key-value store
Document storeDocument store
Graph DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.89
Rank#67  Overall
#8  Key-value stores
Score7.85
Rank#51  Overall
#8  Document stores
Score3.19
Rank#93  Overall
#16  Document stores
#7  Graph DBMS
#14  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.ehcache.orgfirebase.google.com/­products/­firestoreorientdb.orgspark.apache.org/­sql
Technical documentationwww.ehcache.org/­documentationfirebase.google.com/­docs/­firestorewww.orientdb.com/­docs/­last/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperTerracotta Inc, owned by Software AGFatCloudGoogleOrientDB LTD; CallidusCloud; SAPApache Software Foundation
Initial release20092012201720102014
Current release3.10.0, March 20223.2.29, March 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoApache version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#JavaScala
Server operating systemsAll OS with a Java VMWindowshostedAll OS with a Java JDK (>= JDK 6)Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeschema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")yes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nononono
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLnono infoVia inetgration in SQL ServernoSQL-like query language, no joinsSQL-like DML and DDL statements
APIs and other access methodsJCache.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesJavaC#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsyes, Firebase Rules & Cloud FunctionsJava, Javascriptno
Triggersyes infoCache Event Listenersyes infovia applicationsyes, with Cloud FunctionsHooksno
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Serverselectable replication factorMulti-source replicationMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesUsing Cloud Dataflowno infocould be achieved with distributed queries
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes inforelationship in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourcenoyesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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 controlnono 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.Access rights for users and roles; record level security configurableno

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More resources
EhcacheFatDBGoogle Cloud FirestoreOrientDBSpark SQL
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