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DBMS > Amazon DocumentDB vs. Apache Druid vs. Google Cloud Firestore vs. Solr

System Properties Comparison Amazon DocumentDB vs. Apache Druid vs. Google Cloud Firestore vs. Solr

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Druid  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataCloud 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.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument storeRelational DBMS
Time Series DBMS
Document storeSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score42.91
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­documentdbdruid.apache.orgfirebase.google.com/­products/­firestoresolr.apache.org
Technical documentationaws.amazon.com/­documentdb/­resourcesdruid.apache.org/­docs/­latest/­designfirebase.google.com/­docs/­firestoresolr.apache.org/­resources.html
DeveloperApache Software Foundation and contributorsGoogleApache Software Foundation
Initial release2019201220172006
Current release29.0.1, April 20249.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2commercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemshostedLinux
OS X
Unix
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyes infoschema-less columns are supportedschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typing
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.nononoyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoSQL for queryingnoSolr Parallel SQL Interface
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
RESTful HTTP/JSON API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnonoyes, Firebase Rules & Cloud FunctionsJava plugins
Triggersnonoyes, with Cloud Functionsyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infomanual/auto, time-basedShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes, via HDFS, S3 or other storage enginesMulti-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noUsing Cloud Dataflowspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoyesoptimistic locking
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.noyes
User concepts infoAccess controlAccess rights for users and rolesRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.yes

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More resources
Amazon DocumentDBApache DruidGoogle Cloud FirestoreSolr
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