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DBMS > Apache Impala vs. Elasticsearch vs. Spark SQL vs. Typesense

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonElasticsearch  Xexclude from comparisonSpark SQL  Xexclude from comparisonTypesense  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricSpark 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 DBMSSearch engineRelational DBMSSearch engine
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score134.78
Rank#7  Overall
#1  Search engines
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.91
Rank#203  Overall
#14  Search engines
Websiteimpala.apache.orgwww.elastic.co/­elasticsearchspark.apache.org/­sqltypesense.org
Technical documentationimpala.apache.org/­impala-docs.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmltypesense.org/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaElasticApache Software Foundation
Initial release2013201020142015
Current release4.1.0, June 20228.6, January 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoElastic LicenseOpen 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++JavaScalaC++
Server operating systemsLinuxAll OS with a Java VMLinux
OS X
Windows
Linux
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesschema-free infopre-defined schema optional
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyes infoAll search fields are automatically indexednoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Java
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-reduceyesnono
Triggersnoyes infoby using the 'percolation' featureno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesnoneMulti-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceES-Hadoop Connectorno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
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.noMemcached and Redis integrationnoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno

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More resources
Apache ImpalaElasticsearchSpark SQLTypesense
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