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DBMS > Apache Impala vs. Elasticsearch vs. FoundationDB vs. Sequoiadb vs. Spark SQL

System Properties Comparison Apache Impala vs. Elasticsearch vs. FoundationDB vs. Sequoiadb vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonElasticsearch  Xexclude from comparisonFoundationDB  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
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 metricOrdered key-value store. Core features are complimented by layers.NewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSSearch engineDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Document store
Relational DBMS
Relational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score15.06
Rank#39  Overall
#24  Relational DBMS
Score134.79
Rank#7  Overall
#1  Search engines
Score1.50
Rank#166  Overall
#29  Document stores
#27  Key-value stores
#76  Relational DBMS
Score0.50
Rank#264  Overall
#42  Document stores
#121  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Websiteimpala.apache.orgwww.elastic.co/­elasticsearchgithub.com/­apple/­foundationdbwww.sequoiadb.comspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlapple.github.io/­foundationdbwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaElasticFoundationDBSequoiadb Ltd.Apache Software Foundation
Initial release20132010201320132014
Current release4.1.0, June 20228.6, January 20236.2.28, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoElastic LicenseOpen Source infoApache 2.0Open Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++C++Scala
Server operating systemsLinuxAll OS with a Java VMLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-free infosome layers support schemasschema-freeyes
Typing infopredefined data types such as float or dateyesyesno infosome layers support typingyes infooid, date, timestamp, binary, regexyes
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 indexesyesyes infoAll search fields are automatically indexednoyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languagesupported in specific SQL layer onlySQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP/JSON API
proprietary protocol using JSONJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesin SQL-layer onlyJavaScriptno
Triggersnoyes infoby using the 'percolation' featurenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceES-Hadoop Connectornono
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, allLinearizable consistencyEventual Consistency
Foreign keys infoReferential integritynonoin SQL-layer onlynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDDocument is locked during a transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noMemcached and Redis integrationnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnosimple password-based access controlno

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More resources
Apache ImpalaElasticsearchFoundationDBSequoiadbSpark SQL
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