DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon DocumentDB vs. Microsoft Azure AI Search vs. Pinecone vs. Realm

System Properties Comparison Amazon DocumentDB vs. Microsoft Azure AI Search vs. Pinecone vs. Realm

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonPinecone  Xexclude from comparisonRealm  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceSearch-as-a-service for web and mobile app developmentA managed, cloud-native vector databaseA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelDocument storeSearch engineVector DBMSDocument store
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score5.59
Rank#63  Overall
#7  Search engines
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Websiteaws.amazon.com/­documentdbazure.microsoft.com/­en-us/­services/­searchwww.pinecone.iorealm.io
Technical documentationaws.amazon.com/­documentdb/­resourceslearn.microsoft.com/­en-us/­azure/­searchdocs.pinecone.io/­docs/­overviewrealm.io/­docs
DeveloperMicrosoftPinecone Systems, IncRealm, acquired by MongoDB in May 2019
Initial release2019201520192014
Current releaseV1
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source
Cloud-based only infoOnly available as a cloud serviceyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Server operating systemshostedhostedhostedAndroid
Backend: server-less
iOS
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesString, Number, Booleanyes
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 indexesyesyesyes
SQL infoSupport of SQLnononono
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)RESTful HTTP APIRESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
Java
JavaScript
Python
Python.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresnonono inforuns within the applications so server-side scripts are unnecessary
Triggersnonoyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes infoImplicit feature of the cloud servicenone
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 ConsistencyImmediate ConsistencyImmediate 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 operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.nonoyes infoIn-Memory realm
User concepts infoAccess controlAccess rights for users and rolesyes infousing Azure authenticationyes

More information provided by the system vendor

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

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

More resources
Amazon DocumentDBMicrosoft Azure AI SearchPineconeRealm
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

AWS announces Amazon DocumentDB I/O-Optimized
21 November 2023, AWS Blog

AWS announces vector search for Amazon DocumentDB
29 November 2023, AWS Blog

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

Mask sensitive Amazon DocumentDB log data with Amazon CloudWatch Logs data protection | Amazon Web Services
16 April 2024, AWS Blog

provided by Google News

Announcing updates to Azure AI Search to help organizations build and scale generative AI applications
4 April 2024, Microsoft

Shift AI Podcast: How AI is evolving in 2024, with Microsoft Distinguished Engineer Pablo Castro
9 May 2024, GeekWire

Public Preview of Azure OpenAI and AI Search in-app connectors for Logic Apps (Standard) | Azure updates
2 April 2024, Microsoft

Microsoft’s Azure AI Search updated with increased storage, vector index size
5 April 2024, InfoWorld

Microsoft Azure AI adds storage power, large RAG app support
5 April 2024, VentureBeat

provided by Google News

Pinecone’s new serverless database may see few takers, analysts say
17 January 2024, InfoWorld

Pinecone Unveils Serverless Vector Database for Enhanced AI Applications
16 January 2024, Datanami

Pinecone Brings Serverless To Vector Databases
16 January 2024, Forbes

Pinecone: New vector database architecture a 'breakthrough' to curb AI hallucinations
16 January 2024, VentureBeat

Reimagining Vector Databases for the Generative AI Era with Pinecone Serverless on AWS | Amazon Web Services
21 March 2024, AWS Blog

provided by Google News

GDG North Jersey's February Meeting Covers Realm, A New Mobile Database
6 March 2016, njtechweekly.com

MongoDB aims to unify developer experience with launch of MongoDB Cloud
9 June 2020, diginomica

Danish CEO explains Silicon Valley learning curve for European entrepreneurs - San Francisco Business Times
6 October 2016, The Business Journals

Here are the winners of Nordic Startup Awards
31 May 2016, EU-Startups

Is Swift the Future of Server-side Development?
12 September 2017, Solutions Review

provided by Google News



Share this page

Featured Products

RaimaDB logo

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

Milvus logo

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

SingleStore logo

Database for your real-time AI and Analytics Apps.
Try it today.

Neo4j logo

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

Present your product here