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DBMS > Databricks vs. FatDB vs. Geode

System Properties Comparison Databricks vs. FatDB vs. Geode

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonGeode  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 .NET NoSQL DBMS that can integrate with and extend SQL Server.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.86
Rank#134  Overall
#24  Key-value stores
Websitewww.databricks.comgeode.apache.org
Technical documentationdocs.databricks.comgeode.apache.org/­docs
DeveloperDatabricksFatCloudOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.
Initial release201320122002
Current release1.1, February 2017
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses available as Gemfire
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#Java
Server operating systemshostedWindowsAll OS with a Java VM infothe JDK (8 or later) is also required
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyes
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.yesno
Secondary indexesyesyesno
SQL infoSupport of SQLwith Databricks SQLno infoVia inetgration in SQL ServerSQL-like query language (OQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Java Client API
Memcached protocol
RESTful HTTP API
Supported programming languagesPython
R
Scala
C#.Net
All JVM based languages
C++
Groovy
Java
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infovia applicationsuser defined functions
Triggersyes infovia applicationsyes infoCache Event Listeners
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyes, on a single node
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights per client and object definable
More information provided by the system vendor
DatabricksFatDBGeode
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksFatDBGeode
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