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DBMS > Amazon DocumentDB vs. Apache Solr vs. Realm

System Properties Comparison Amazon DocumentDB vs. Apache Solr vs. Realm

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Solr  Xexclude from comparisonRealm  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA widely used distributed, scalable search engine based on Apache LuceneA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelDocument storeSearch engineDocument store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.80
Rank#126  Overall
#24  Document stores
Score32.79
Rank#23  Overall
#3  Search engines
Score6.80
Rank#51  Overall
#8  Document stores
Websiteaws.amazon.com/­documentdbsolr.apache.orgrealm.io
Technical documentationaws.amazon.com/­documentdb/­resourcessolr.apache.org/­resources.htmlrealm.io/­docs
DeveloperApache Software FoundationRealm, acquired by MongoDB in May 2019
Initial release201920062014
Current release9.6.1, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemshostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Android
Backend: server-less
iOS
Windows
Data schemeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic 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.noyesno
Secondary indexesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnoSolr Parallel SQL Interfaceno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Java API
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresnoJava pluginsno inforuns within the applications so server-side scripts are unnecessary
Triggersnoyes infoUser configurable commands triggered on index changesyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)spark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoIn-Memory realm
User concepts infoAccess controlAccess rights for users and rolesyesyes

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