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DBMS > Ehcache vs. FatDB vs. Spark SQL vs. YugabyteDB

System Properties Comparison Ehcache vs. FatDB vs. Spark SQL vs. YugabyteDB

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonYugabyteDB  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 processingHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelKey-value storeDocument store
Key-value store
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.89
Rank#67  Overall
#8  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.91
Rank#102  Overall
#51  Relational DBMS
Websitewww.ehcache.orgspark.apache.org/­sqlwww.yugabyte.com
Technical documentationwww.ehcache.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperTerracotta Inc, owned by Software AGFatCloudApache Software FoundationYugabyte Inc.
Initial release2009201220142017
Current release3.10.0, March 20223.5.0 ( 2.13), September 20232.19, September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageJavaC#ScalaC and C++
Server operating systemsAll OS with a Java VMWindowsLinux
OS X
Windows
Linux
OS X
Data schemeschema-freeschema-freeyesdepending on used data model
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 indexesnoyesnoyes
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSQL-like DML and DDL statementsyes, PostgreSQL compatible
APIs and other access methodsJCache.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languagesJavaC#Java
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsnoyes infosql, plpgsql, C
Triggersyes infoCache Event Listenersyes infovia applicationsnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingyes, utilizing Spark CoreHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Serverselectable replication factornoneBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
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
Strong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourcenonoDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyesyes infobased on RocksDB
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 applicationsnoyes
More information provided by the system vendor
EhcacheFatDBSpark SQLYugabyteDB
Specific characteristicsYugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantagesPostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more
Typical application scenariosSystems of record and engagement for cloud native applications that require resilience,...
» more
Market metrics2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsApache 2.0 license for the database
» more

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EhcacheFatDBSpark SQLYugabyteDB
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