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DBMS > Ehcache vs. FatDB vs. Google Cloud Datastore vs. Spark SQL

System Properties Comparison Ehcache vs. FatDB vs. Google Cloud Datastore vs. Spark SQL

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeDocument store
Key-value store
Document storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.64
Rank#68  Overall
#8  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.ehcache.orgcloud.google.com/­datastorespark.apache.org/­sql
Technical documentationwww.ehcache.org/­documentationcloud.google.com/­datastore/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperTerracotta Inc, owned by Software AGFatCloudGoogleApache Software Foundation
Initial release2009201220082014
Current release3.10.0, March 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC#Scala
Server operating systemsAll OS with a Java VMWindowshostedLinux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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 indexesnoyesyesno
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSQL-like query language (GQL)SQL-like DML and DDL statements
APIs and other access methodsJCache.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesJavaC#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsusing Google App Engineno
Triggersyes infoCache Event Listenersyes infovia applicationsCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Serverselectable replication factorMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourcenoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
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.yesnono
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 (IAM)no

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More resources
EhcacheFatDBGoogle Cloud DatastoreSpark SQL
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