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DBMS > Amazon SimpleDB vs. Apache Impala vs. Elasticsearch vs. FoundationDB vs. Spark SQL

System Properties Comparison Amazon SimpleDB vs. Apache Impala vs. Elasticsearch vs. FoundationDB vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache Impala  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreAnalytic 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.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeRelational DBMSSearch engineDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score13.77
Rank#40  Overall
#24  Relational 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
Websiteaws.amazon.com/­simpledbimpala.apache.orgwww.elastic.co/­elasticsearchgithub.com/­apple/­foundationdbspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­simpledbimpala.apache.org/­impala-docs.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlapple.github.io/­foundationdbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaElasticFoundationDBApache Software Foundation
Initial release20072013201020132014
Current release4.1.0, June 20228.6, January 20236.2.28, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoElastic LicenseOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++Scala
Server operating systemshostedLinuxAll OS with a Java VMLinux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeyesschema-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 datenoyesyesno 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.nonono
Secondary indexesyes infoAll columns are indexed automaticallyyesyes infoAll search fields are automatically indexednono
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query languagesupported in specific SQL layer onlySQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
All 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
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyesin SQL-layer onlyno
Triggersnonoyes infoby using the 'percolation' featurenono
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factoryesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceES-Hadoop Connectorno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual 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 integritynononoin SQL-layer onlyno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationnonoACIDno
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 integrationno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles infobased on Apache Sentry and Kerberosnono

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More resources
Amazon SimpleDBApache ImpalaElasticsearchFoundationDBSpark SQL
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