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DBMS > Elasticsearch vs. FatDB vs. Google Cloud Firestore vs. Spark SQL

System Properties Comparison Elasticsearch vs. FatDB vs. Google Cloud Firestore vs. Spark SQL

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonSpark SQL  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from 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 metricA .NET NoSQL DBMS that can integrate with and extend SQL Server.Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelSearch engineDocument store
Key-value store
Document storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score7.85
Rank#51  Overall
#8  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.elastic.co/­elasticsearchfirebase.google.com/­products/­firestorespark.apache.org/­sql
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlfirebase.google.com/­docs/­firestorespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperElasticFatCloudGoogleApache Software Foundation
Initial release2010201220172014
Current release8.6, January 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC#Scala
Server operating systemsAll OS with a Java VMWindowshostedLinux
OS X
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeschema-freeyes
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 indexesyes infoAll search fields are automatically indexedyesyesno
SQL infoSupport of SQLSQL-like query languageno infoVia inetgration in SQL ServernoSQL-like DML and DDL statements
APIs and other access methodsJava API
RESTful HTTP/JSON API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyes infovia applicationsyes, Firebase Rules & Cloud Functionsno
Triggersyes infoby using the 'percolation' featureyes infovia applicationsyes, with Cloud Functionsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop ConnectoryesUsing Cloud Dataflow
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, allEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesno
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 integrationno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.no

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More resources
ElasticsearchFatDBGoogle Cloud FirestoreSpark SQL
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