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DBMS > Databricks vs. Riak TS vs. RRDtool vs. Spark SQL

System Properties Comparison Databricks vs. Riak TS vs. RRDtool vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonRiak TS  Xexclude from comparisonRRDtool  Xexclude from comparisonSpark SQL  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 KVIndustry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Relational DBMS
Time Series DBMSTime Series DBMSRelational DBMS
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
Score1.90
Rank#132  Overall
#11  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.databricks.comoss.oetiker.ch/­rrdtoolspark.apache.org/­sql
Technical documentationdocs.databricks.comwww.tiot.jp/­riak-docs/­riak/­ts/­latestoss.oetiker.ch/­rrdtool/­docspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksOpen Source, formerly Basho TechnologiesTobias OetikerApache Software Foundation
Initial release2013201519992014
Current release3.0.0, September 20221.8.0, 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoGPL V2 and FLOSSOpen Source infoApache 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 infoImplementations in Java (e.g. RRD4J) and C# availableScala
Server operating systemshostedLinux
OS X
HP-UX
Linux
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or datenoNumeric data onlyyes
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 infoExporting into and restoring from XML files possibleno
Secondary indexesyesrestrictednono
SQL infoSupport of SQLwith Databricks SQLyes, limitednoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP API
Native Erlang Interface
in-process shared library
Pipes
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 infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesErlangnono
Triggersyes infopre-commit hooks and post-commit hooksnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistencynone
Foreign keys infoReferential integrityno infolinks between datasets can be storednono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoby using the rrdcached daemonyes
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.noyesno
User concepts infoAccess controlnonono
More information provided by the system vendor
DatabricksRiak TSRRDtoolSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksRiak TSRRDtoolSpark SQL
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