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DBMS > Databricks vs. Riak TS vs. RocksDB vs. Tkrzw

System Properties Comparison Databricks vs. Riak TS vs. RocksDB vs. Tkrzw

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonRiak TS  Xexclude from comparisonRocksDB  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.Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KVEmbeddable 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 Cabinet
Primary database modelDocument store
Relational DBMS
Time Series DBMSKey-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
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Score3.65
Rank#85  Overall
#11  Key-value stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.databricks.comrocksdb.orgdbmx.net/­tkrzw
Technical documentationdocs.databricks.comwww.tiot.jp/­riak-docs/­riak/­ts/­latestgithub.com/­facebook/­rocksdb/­wiki
DeveloperDatabricksOpen Source, formerly Basho TechnologiesFacebook, Inc.Mikio Hirabayashi
Initial release2013201520132020
Current release3.0.0, September 20228.11.4, April 20240.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoBSDOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC++C++
Server operating systemshostedLinux
OS X
LinuxLinux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-free
Typing infopredefined data types such as float or datenonono
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.yesnonono
Secondary indexesyesrestrictedno
SQL infoSupport of SQLwith Databricks SQLyes, limitednono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP API
Native Erlang Interface
C++ API
Java API
Supported programming languagesPython
R
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C
C++
Go
Java
Perl
Python
Ruby
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesErlangnono
Triggersyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factoryesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infolinks between datasets can be storednono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyes
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 controlnonono
More information provided by the system vendor
DatabricksRiak TSRocksDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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3rd partiesSpeedb: A high performance RocksDB-compliant key-value store optimized for write-intensive workloads.
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More resources
DatabricksRiak TSRocksDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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