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DBMS > Databricks vs. RocksDB vs. Tkrzw vs. Transwarp KunDB

System Properties Comparison Databricks vs. RocksDB vs. Tkrzw vs. Transwarp KunDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonRocksDB  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonTranswarp KunDB  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 persistent key-value store optimized for fast storage (flash and RAM)A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetOLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle
Primary database modelDocument store
Relational DBMS
Key-value storeKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score2.84
Rank#97  Overall
#16  Key-value stores
Score0.00
Rank#385  Overall
#61  Key-value stores
Score0.04
Rank#362  Overall
#154  Relational DBMS
Websitewww.databricks.comrocksdb.orgdbmx.net/­tkrzwwww.transwarp.cn/­en/­product/­kundb
Technical documentationdocs.databricks.comgithub.com/­facebook/­rocksdb/­wiki
DeveloperDatabricksFacebook, Inc.Mikio HirabayashiTranswarp
Initial release201320132020
Current release9.4.0, June 20240.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemshostedLinuxLinux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes
Typing infopredefined data types such as float or datenonoyes
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 indexesyesnoyes
SQL infoSupport of SQLwith Databricks SQLnonoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
C++ API
Java API
Supported programming languagesPython
R
Scala
C
C++
Go
Java
Perl
Python
Ruby
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonoyes
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing specific database classes
User concepts infoAccess controlnonoyes
More information provided by the system vendor
DatabricksRocksDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetTranswarp KunDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksRocksDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetTranswarp KunDB
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