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

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

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonRiak TS  Xexclude from comparisonRocksDB  Xexclude from comparisonSnowflake  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)Cloud-based data warehousing service for structured and semi-structured dataA 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 storeRelational DBMSKey-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
Score0.28
Rank#307  Overall
#27  Time Series DBMS
Score3.41
Rank#86  Overall
#11  Key-value stores
Score130.36
Rank#8  Overall
#5  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.databricks.comrocksdb.orgwww.snowflake.comdbmx.net/­tkrzw
Technical documentationdocs.databricks.comwww.tiot.jp/­riak-docs/­riak/­ts/­latestgithub.com/­facebook/­rocksdb/­wikidocs.snowflake.net/­manuals/­index.html
DeveloperDatabricksOpen Source, formerly Basho TechnologiesFacebook, Inc.Snowflake Computing Inc.Mikio Hirabayashi
Initial release20132015201320142020
Current release3.0.0, September 20229.2.1, May 20240.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoBSDcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangC++C++
Server operating systemshostedLinux
OS X
LinuxhostedLinux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes infosupport of semi-structured data formats (JSON, XML, Avro)schema-free
Typing infopredefined data types such as float or datenonoyesno
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.yesnonoyesno
Secondary indexesyesrestrictedno
SQL infoSupport of SQLwith Databricks SQLyes, limitednoyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP API
Native Erlang Interface
C++ API
Java API
CLI Client
JDBC
ODBC
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
JavaScript (Node.js)
Python
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesErlangnouser defined functionsno
Triggersyes infopre-commit hooks and post-commit hooksno infosimilar concept for controling cloud resourcesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningyesnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factoryesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infolinks between datasets can be storednoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes infousing specific database classes
User concepts infoAccess controlnonoUsers with fine-grained authorization concept, user roles and pluggable authenticationno
More information provided by the system vendor
DatabricksRiak TSRocksDBSnowflakeTkrzw 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
DatabricksRiak TSRocksDBSnowflakeTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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