DB-EnginesextremeDB - solve IoT connectivity disruptionsEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by Redgate Software

DBMS > Amazon DocumentDB vs. Amazon DynamoDB vs. Milvus vs. WakandaDB

System Properties Comparison Amazon DocumentDB vs. Amazon DynamoDB vs. Milvus vs. WakandaDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAmazon DynamoDB  Xexclude from comparisonMilvus  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHosted, scalable database service by Amazon with the data stored in Amazons cloudA DBMS designed for efficient storage of vector data and vector similarity searchesWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument storeDocument store
Key-value store
Vector DBMSObject oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#124  Overall
#22  Document stores
Score70.06
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score3.01
Rank#89  Overall
#4  Vector DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websiteaws.amazon.com/­documentdbaws.amazon.com/­dynamodbmilvus.iowakanda.github.io
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.aws.amazon.com/­dynamodbmilvus.io/­docs/­overview.mdwakanda.github.io/­doc
DeveloperAmazonWakanda SAS
Initial release2019201220192012
Current release2.4.4, May 20242.7.0 (April 29, 2019), April 2019
License infoCommercial or Open Sourcecommercialcommercial infofree tier for a limited amount of database operationsOpen Source infoApache Version 2.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC++, GoC++, JavaScript
Server operating systemshostedhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringyes
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.nonono
Secondary indexesyesyesno
SQL infoSupport of SQLnononono
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)RESTful HTTP APIRESTful HTTP APIRESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript
Server-side scripts infoStored proceduresnononoyes
Triggersnoyes infoby integration with AWS Lambdanoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone
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)no infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency infocan be specified for read operations
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate 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 operationsACID infoACID across one or more tables within a single AWS account and regionnoACID
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.yesno
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Role based access control and fine grained access rightsyes
More information provided by the system vendor
Amazon DocumentDBAmazon DynamoDBMilvusWakandaDB
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services
3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Amazon DocumentDBAmazon DynamoDBMilvusWakandaDB
DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Increased popularity for consuming DBMS services out of the cloud
2 October 2015, Paul Andlinger

show all

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

Unlock the power of parallel indexing in Amazon DocumentDB
19 June 2024, AWS Blog

AWS announces Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service
16 May 2024, AWS Blog

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0
15 April 2024, AWS Blog

Optimizing costs on Amazon DocumentDB using event-driven architecture and the AWS EventBridge Terraform module
23 August 2024, AWS Blog

Unlock the power of Amazon DocumentDB text search with real-world use cases
5 March 2024, AWS Blog

provided by Google News

How Samsung Cloud optimized Amazon DynamoDB costs | Amazon Web Services
19 September 2024, AWS Blog

Migrating Uber's Ledger Data from DynamoDB to LedgerStore
11 April 2024, Uber

Join the preview of attribute-based access control for Amazon DynamoDB | Amazon Web Services
3 September 2024, AWS Blog

Achieve near real-time analytics on Amazon DynamoDB with SingleStore
16 September 2024, AWS Blog

Faster development with Amazon DynamoDB and Amazon Q Developer
12 September 2024, AWS Blog

provided by Google News

How NVIDIA GPU Acceleration Supercharged Milvus Vector Database
26 March 2024, The New Stack

AI-Powered Search Engine With Milvus Vector Database on Vultr - SitePoint
30 August 2024, SitePoint

IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI
9 April 2024, IBM

10 top vector database options for similarity searches
8 August 2024, TechTarget

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

provided by Google News



Share this page

Featured Products

SingleStore logo

The data platform to build your intelligent applications.
Try it free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Present your product here