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DBMS > Apache Impala vs. Databricks vs. DataFS

System Properties Comparison Apache Impala vs. Databricks vs. DataFS

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonDataFS  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopThe 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.All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.
Primary database modelRelational DBMSDocument store
Relational DBMS
Object oriented DBMS
Secondary database modelsDocument storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.09
Rank#360  Overall
#17  Object oriented DBMS
Websiteimpala.apache.orgwww.databricks.comnewdatabase.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comdev.mobiland.com/­Overview.xsp
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksMobiland AG
Initial release201320132018
Current release4.1.0, June 20221.1.263, October 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemsLinuxhostedWindows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)
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.noyesno
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
.NET Client API
Proprietary client DLL
WinRT client
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
.Net
C
C#
C++
VB.Net
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregates
Triggersnono, except callback-events from server when changes happened
Partitioning methods infoMethods for storing different data on different nodesShardingProprietary Sharding system
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosWindows-Profile
More information provided by the system vendor
Apache ImpalaDatabricksDataFS
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache ImpalaDatabricksDataFS
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12 June 2024, SiliconANGLE News

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12 June 2024, VentureBeat

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