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DBMS > Databricks vs. RRDtool vs. Spark SQL

System Properties Comparison Databricks vs. RRDtool vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatabricks  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.Industry 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 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
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.comoss.oetiker.ch/­rrdtool/­docspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksTobias OetikerApache Software Foundation
Initial release201319992014
Current release1.8.0, 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL V2 and FLOSSOpen Source infoApache 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 infoImplementations in Java (e.g. RRD4J) and C# availableScala
Server operating systemshostedHP-UX
Linux
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateNumeric 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.yesno infoExporting into and restoring from XML files possibleno
Secondary indexesyesnono
SQL infoSupport of SQLwith Databricks SQLnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
in-process shared library
Pipes
JDBC
ODBC
Supported programming languagesPython
R
Scala
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 aggregatesnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistencynone
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyes infoby using the rrdcached daemonyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnono
More information provided by the system vendor
DatabricksRRDtoolSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksRRDtoolSpark SQL
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