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DBMS > Databricks vs. LevelDB vs. Tkrzw

System Properties Comparison Databricks vs. LevelDB vs. Tkrzw

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonLevelDB  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.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesA 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
Key-value storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.databricks.comgithub.com/­google/­leveldbdbmx.net/­tkrzw
Technical documentationdocs.databricks.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperDatabricksGoogleMikio Hirabayashi
Initial release201320112020
Current release1.23, February 20210.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen 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++C++
Server operating systemshostedIllumos
Linux
OS X
Windows
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or datenono
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
Supported programming languagesPython
R
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnonenone
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 integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infousing specific database classes
User concepts infoAccess controlnono
More information provided by the system vendor
DatabricksLevelDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksLevelDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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