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DBMS > Elasticsearch vs. FoundationDB vs. GigaSpaces vs. Spark SQL

System Properties Comparison Elasticsearch vs. FoundationDB vs. GigaSpaces vs. Spark SQL

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonFoundationDB  Xexclude from comparisonGigaSpaces  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.
DescriptionA 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.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelSearch engineDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Graph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.elastic.co/­elasticsearchgithub.com/­apple/­foundationdbwww.gigaspaces.comspark.apache.org/­sql
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlapple.github.io/­foundationdbdocs.gigaspaces.com/­latest/­landing.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperElasticFoundationDBGigaspaces TechnologiesApache Software Foundation
Initial release2010201320002014
Current release8.6, January 20236.2.28, November 202015.5, September 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen Source infoApache 2.0Open Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java, C++, .NetScala
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
Linux
macOS
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-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 dateyesno infosome layers support typingyesyes
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 infoXML can be used for describing objects metadatano
Secondary indexesyes infoAll search fields are automatically indexednoyesno
SQL infoSupport of SQLSQL-like query languagesupported in specific SQL layer onlySQL-99 for query and DML statementsSQL-like DML and DDL statements
APIs and other access methodsJava API
RESTful HTTP/JSON API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
Supported programming languages.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
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesin SQL-layer onlyyesno
Triggersyes infoby using the 'percolation' featurenoyes, event driven architectureno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectornoyes infoMap-Reduce pattern can be built with XAP task executors
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allLinearizable consistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANY
Foreign keys infoReferential integritynoin SQL-layer onlynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
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.Memcached and Redis integrationyesno
User concepts infoAccess controlnoRole-based access controlno

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More resources
ElasticsearchFoundationDBGigaSpacesSpark SQL
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