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DBMS > Amazon DocumentDB vs. Geode vs. Lovefield vs. Solr

System Properties Comparison Amazon DocumentDB vs. Geode vs. Lovefield vs. Solr

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGeode  Xexclude from comparisonLovefield  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesEmbeddable relational database for web apps written in pure JavaScriptA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument storeKey-value storeRelational DBMSSearch 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
Score1.92
Rank#131  Overall
#23  Key-value stores
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­documentdbgeode.apache.orggoogle.github.io/­lovefieldsolr.apache.org
Technical documentationaws.amazon.com/­documentdb/­resourcesgeode.apache.org/­docsgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsolr.apache.org/­resources.html
DeveloperOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GoogleApache Software Foundation
Initial release2019200220142006
Current release1.1, February 20172.1.12, February 20179.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoApache 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScriptJava
Server operating systemshostedAll OS with a Java VM infothe JDK (8 or later) is also requiredserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-freeyesyes 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 indexesyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoSQL-like query language (OQL)SQL-like query language infovia JavaScript builder patternSolr Parallel SQL Interface
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Java Client API
Memcached protocol
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
All JVM based languages
C++
Groovy
Java
Scala
JavaScript.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnouser defined functionsnoJava plugins
Triggersnoyes infoCache Event ListenersUsing read-only observersyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replicationnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsyes, on a single nodeACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing MemoryDByes
User concepts infoAccess controlAccess rights for users and rolesAccess rights per client and object definablenoyes

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Amazon DocumentDBGeodeLovefieldSolr
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