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DBMS > Apache Drill vs. Impala vs. Spark SQL

System Properties Comparison Apache Drill vs. Impala vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonImpala  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageAnalytic DBMS for HadoopSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.82
Rank#85  Overall
#16  Document stores
#43  Relational DBMS
Score14.80
Rank#37  Overall
#22  Relational DBMS
Score16.56
Rank#34  Overall
#21  Relational DBMS
Websitedrill.apache.orgwww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.htmlspark.apache.org/­sql
Technical documentationdrill.apache.org/­docswww.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationClouderaApache Software Foundation
Initial release201220132014
Current release1.14, August 20183.0.0, May 2018v2.4.0, November 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeschema-freeyesyes
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.nonono
Secondary indexesnoyesno
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP API
JDBC
ODBC
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC++All languages supporting JDBC/ODBCJava
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infouser defined functions and integration of map-reduceno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourcenono
User concepts infoAccess controlDepending on the underlying data sourceAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno

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More resources
Apache DrillImpalaSpark SQL
Conferences and events

Spark + AI Summit
San Francisco, California, 23-25 April 2019

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