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DBMS > Databricks vs. DuckDB vs. Spark SQL

System Properties Comparison Databricks vs. DuckDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDuckDB  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.An embeddable, in-process, column-oriented SQL OLAP RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.57
Rank#74  Overall
#40  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.databricks.comduckdb.orgspark.apache.org/­sql
Technical documentationdocs.databricks.comduckdb.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksApache Software Foundation
Initial release201320182014
Current release0.10, February 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicenseOpen 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++Scala
Server operating systemshostedserver-lessLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyes
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 indexesyesyesno
SQL infoSupport of SQLwith Databricks SQLyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
JDBC
ODBC
Supported programming languagesPython
R
Scala
C
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
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
DatabricksDuckDBSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDuckDBSpark SQL
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