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DBMS > Apache Impala vs. Databricks vs. MaxDB

System Properties Comparison Apache Impala vs. Databricks vs. MaxDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonMaxDB infoformerly named Adabas-D  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.A robust and reliable RDBMS optimized to run all major SAP solutions
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.39
Rank#41  Overall
#25  Relational DBMS
Score87.68
Rank#13  Overall
#2  Document stores
#9  Relational DBMS
Score2.16
Rank#113  Overall
#54  Relational DBMS
Websiteimpala.apache.orgwww.databricks.commaxdb.sap.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.commaxdb.sap.com/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksSAP, acquired from Software AG (Adabas-D) in 1997
Initial release201320131984
Current release4.1.0, June 20227.9.10.12, February 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemsLinuxhostedAIX
HP-UX
Linux
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yes
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 indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
WebDAV
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
.Net
C#
Java
Perl
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesyes
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSource-replica replication
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 Kerberosfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaDatabricksMaxDB infoformerly named Adabas-D
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache ImpalaDatabricksMaxDB infoformerly named Adabas-D
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