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DBMS > Apache Drill vs. Apache Impala vs. Spark SQL vs. SWC-DB

System Properties Comparison Apache Drill vs. Apache Impala vs. Spark SQL vs. SWC-DB

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Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonApache Impala  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  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 processingA high performance, scalable Wide Column DBMS
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSWide column store
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#127  Overall
#23  Document stores
#60  Relational DBMS
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websitedrill.apache.orgimpala.apache.orgspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdrill.apache.org/­docsimpala.apache.org/­impala-docs.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationAlex Kashirin
Initial release2012201320142020
Current release1.20.3, January 20234.1.0, June 20223.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2Open Source infoApache 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Windows
Linux
Data schemeschema-freeyesyesschema-free
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.nononono
Secondary indexesnoyesno
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantSQL-like DML and DDL statementsSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
Thrift
Supported programming languagesC++All languages supporting JDBC/ODBCJava
Python
R
Scala
C++
Server-side scripts infoStored proceduresuser defined functionsyes infouser defined functions and integration of map-reducenono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreSharding
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 MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourcenonono
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 DrillApache ImpalaSpark SQLSWC-DB infoSuper Wide Column Database
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