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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDataFS  Xexclude from comparisonElasticsearch  Xexclude from comparisonFoundationDB  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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 HadoopAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.A 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.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSObject oriented DBMSSearch engineDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMS
Secondary database modelsDocument storeGraph DBMSDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgnewdatabase.comwww.elastic.co/­elasticsearchgithub.com/­apple/­foundationdbspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmldev.mobiland.com/­Overview.xspwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlapple.github.io/­foundationdbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMobiland AGElasticFoundationDBApache Software Foundation
Initial release20132018201020132014
Current release4.1.0, June 20221.1.263, October 20228.6, January 20236.2.28, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoElastic LicenseOpen Source infoApache 2.0Open 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++Scala
Server operating systemsLinuxWindowsAll OS with a Java VMLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-free infosome layers support schemasyes
Typing infopredefined data types such as float or dateyesyesyesno infosome layers support typingyes
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 indexesyesnoyes infoAll search fields are automatically indexednono
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query languagesupported in specific SQL layer onlySQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
.NET Client API
Proprietary client DLL
WinRT client
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C#
C++
VB.Net
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesin SQL-layer onlyno
Triggersnono, except callback-events from server when changes happenedyes infoby using the 'percolation' featurenono
Partitioning methods infoMethods for storing different data on different nodesShardingProprietary Sharding systemShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoES-Hadoop Connectorno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allLinearizable consistency
Foreign keys infoReferential integritynoyesnoin SQL-layer onlyno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
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.nonoMemcached and Redis integrationno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosWindows-Profilenono

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More resources
Apache ImpalaDataFSElasticsearchFoundationDBSpark SQL
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