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DBMS > Amazon DocumentDB vs. Heroic vs. Tkrzw vs. VictoriaMetrics

System Properties Comparison Amazon DocumentDB vs. Heroic vs. Tkrzw vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonHeroic  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelDocument storeTime Series DBMSKey-value storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websiteaws.amazon.com/­documentdbgithub.com/­spotify/­heroicdbmx.net/­tkrzwvictoriametrics.com
Technical documentationaws.amazon.com/­documentdb/­resourcesspotify.github.io/­heroicdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperSpotifyMikio HirabayashiVictoriaMetrics
Initial release2019201420202018
Current release0.9.3, August 2020v1.91, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Go
Server operating systemshostedLinux
macOS
FreeBSD
Linux
macOS
OpenBSD
Data schemeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesno
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.nononono
Secondary indexesyesyes infovia Elasticsearch
SQL infoSupport of SQLnononono
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)HQL (Heroic Query Language, a JSON-based language)
HTTP API
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnononono
Triggersnononono
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 replicasyesnoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate 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 operationsnono
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 infousing specific database classesno
User concepts infoAccess controlAccess rights for users and rolesno

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More resources
Amazon DocumentDBHeroicTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetVictoriaMetrics
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