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

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

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEhcache  Xexclude from comparisonFatDB  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.
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A 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 processing
Primary database modelDocument store
Relational DBMS
Key-value storeDocument store
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.64
Rank#68  Overall
#8  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.databricks.comwww.ehcache.orgspark.apache.org/­sql
Technical documentationdocs.databricks.comwww.ehcache.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksTerracotta Inc, owned by Software AGFatCloudApache Software Foundation
Initial release2013200920122014
Current release3.10.0, March 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#Scala
Server operating systemshostedAll OS with a Java VMWindowsLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesnono
Secondary indexesyesnoyesno
SQL infoSupport of SQLwith Databricks SQLnono infoVia inetgration in SQL ServerSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JCache.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Supported programming languagesPython
R
Scala
JavaC#Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes infovia applicationsno
Triggersyes infoCache Event Listenersyes infovia applicationsno
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoby using Terracotta Serverselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infosupports JTA and can work as an XA resourcenono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnono infoCan implement custom security layer via applicationsno
More information provided by the system vendor
DatabricksEhcacheFatDBSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksEhcacheFatDBSpark SQL
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