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DBMS > Amazon DocumentDB vs. InfluxDB vs. Microsoft Azure Cosmos DB vs. Solr vs. Tkrzw

System Properties Comparison Amazon DocumentDB vs. InfluxDB vs. Microsoft Azure Cosmos DB vs. Solr vs. Tkrzw

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonInfluxDB  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonSolr  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceDBMS for storing time series, events and metricsGlobally distributed, horizontally scalable, multi-model database serviceA widely used distributed, scalable search engine based on Apache LuceneA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument storeTime Series DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Search engineKey-value store
Secondary database modelsSpatial DBMS infowith GEO packageSpatial DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Score29.04
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score42.91
Rank#24  Overall
#3  Search engines
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteaws.amazon.com/­documentdbwww.influxdata.com/­products/­influxdb-overviewazure.microsoft.com/­services/­cosmos-dbsolr.apache.orgdbmx.net/­tkrzw
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.influxdata.com/­influxdblearn.microsoft.com/­azure/­cosmos-dbsolr.apache.org/­resources.html
DeveloperMicrosoftApache Software FoundationMikio Hirabayashi
Initial release20192013201420062020
Current release2.7.6, April 20249.6.0, April 20240.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoMIT-License; commercial enterprise version availablecommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaC++
Server operating systemshostedLinux
OS X infothrough Homebrew
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
macOS
Data schemeschema-freeschema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or dateyesNumeric data and Stringsyes infoJSON typesyes infosupports customizable data types and automatic typingno
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.nonoyesno
Secondary indexesyesnoyes infoAll properties auto-indexed by defaultyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoSQL-like query languageSQL-like query languageSolr Parallel SQL Interfaceno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)HTTP API
JSON over UDP
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Java API
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnonoJavaScriptJava pluginsno
TriggersnonoJavaScriptyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoin enterprise version onlySharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication factor infoin enterprise version onlyyes infoImplicit feature of the cloud serviceyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*spark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoMulti-item ACID transactions with snapshot isolation within a partitionoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoDepending on used storage engineyesyes infousing specific database classes
User concepts infoAccess controlAccess rights for users and rolessimple rights management via user accountsAccess rights can be defined down to the item levelyesno
More information provided by the system vendor
Amazon DocumentDBInfluxDBMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSolrTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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More resources
Amazon DocumentDBInfluxDBMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSolrTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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