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DBMS > Databricks vs. DataFS vs. Tkrzw

System Properties Comparison Databricks vs. DataFS vs. Tkrzw

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDataFS  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
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.All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument store
Relational DBMS
Object oriented DBMSKey-value store
Secondary database modelsGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.databricks.comnewdatabase.comdbmx.net/­tkrzw
Technical documentationdocs.databricks.comdev.mobiland.com/­Overview.xsp
DeveloperDatabricksMobiland AGMikio Hirabayashi
Initial release201320182020
Current release1.1.263, October 20220.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemshostedWindowsLinux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-free
Typing infopredefined data types such as float or dateyesno
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 indexesyesno
SQL infoSupport of SQLwith Databricks SQLnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
Proprietary client DLL
WinRT client
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
VB.Net
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesno
Triggersno, except callback-events from server when changes happenedno
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
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.nonoyes infousing specific database classes
User concepts infoAccess controlWindows-Profileno
More information provided by the system vendor
DatabricksDataFSTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksDataFSTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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