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DBMS > Apache Impala vs. Databricks vs. Spark SQL vs. Teradata

System Properties Comparison Apache Impala vs. Databricks vs. Spark SQL vs. Teradata

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  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.Spark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
Time Series 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
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websiteimpala.apache.orgwww.databricks.comspark.apache.org/­sqlwww.teradata.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksApache Software FoundationTeradata
Initial release2013201320141984
Current release4.1.0, June 20223.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemsLinuxhostedLinux
OS X
Windows
hosted
Linux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyesyes
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.noyesnoyes
Secondary indexesyesyesnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLSQL-like DML and DDL statementsyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
Java
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesnoyes infoUDFs, stored procedures, table functions in parallel
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesnoneMulti-source replication
Source-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 integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnofine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaDatabricksSpark SQLTeradata
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache ImpalaDatabricksSpark SQLTeradata
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