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DBMS > Ehcache vs. Faircom DB vs. FatDB vs. Google Cloud Firestore vs. Spark SQL

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

Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonFaircom DB infoformerly c-treeACE  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 optionsNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.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 storeKey-value store
Relational DBMS
Document 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
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.ehcache.orgwww.faircom.com/­products/­faircom-dbfirebase.google.com/­products/­firestorespark.apache.org/­sql
Technical documentationwww.ehcache.org/­documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlfirebase.google.com/­docs/­firestorespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperTerracotta Inc, owned by Software AGFairCom CorporationFatCloudGoogleApache Software Foundation
Initial release20091979201220172014
Current release3.10.0, March 2022V12, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercial infoRestricted, free version availablecommercialcommercialOpen 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 languageJavaANSI C, C++C#Scala
Server operating systemsAll OS with a Java VMAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
WindowshostedLinux
OS X
Windows
Data schemeschema-freeschema free, schema optional, schema required, partial schema,schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyesyes
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 SQLnoyes, ANSI SQL with proprietary extensionsno infoVia inetgration in SQL ServernoSQL-like DML and DDL statements
APIs and other access methodsJCacheADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
.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 languagesJava.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++yes infovia applicationsyes, Firebase Rules & Cloud Functionsno
Triggersyes infoCache Event Listenersyesyes infovia applicationsyes, with Cloud Functionsno
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Serveryes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).selectable 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
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourcetunable from ACID to Eventually Consistentnoyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlnoFine grained access rights according to SQL-standard with additional protections for filesno 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
EhcacheFaircom DB infoformerly c-treeACEFatDBGoogle Cloud FirestoreSpark SQL
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