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DBMS > Apache Impala vs. Spark SQL vs. Typesense

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonSpark SQL  Xexclude from comparisonTypesense  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopSpark SQL is a component on top of 'Spark Core' for structured data processingA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelRelational DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.79
Rank#210  Overall
#14  Search engines
Websiteimpala.apache.orgspark.apache.org/­sqltypesense.org
Technical documentationimpala.apache.org/­impala-docs.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmltypesense.org/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation
Initial release201320142015
Current release4.1.0, June 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++
Server operating systemsLinuxLinux
OS X
Windows
Linux
Data schemeyesyesschema-free infopre-defined schema optional
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.nono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCJava
Python
R
Scala
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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 persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno

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More resources
Apache ImpalaSpark SQLTypesense
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