MongoDB/devcenter-articles huggingface dataset:
# MongoDB Field Level Encryption is now Available for Rust applications

We have some exciting news to announce for Rust developers. Our 2.4.1 release of the MongoDB Rust driver brings a raft of new, innovative features for developers building Rust applications. 

## Field Level Encryption for Rust Applications
This one has been a long time coming. The 2.4.1 version of the MongoDB Rust driver contains field level encryption capabilities - both client side field level encryption and queryable encryption. Starting with MongoDB 4.2, client-side field level encryption allows an application to encrypt specific data fields in addition to pre-existing MongoDB encryption features such as Encryption at Rest and TLS/SSL (Transport Encryption).

With field level encryption, applications can encrypt fields in documents prior to transmitting data over the wire to the server. Client-side field level encryption supports workloads where applications must guarantee that unauthorized parties, including server administrators, cannot read the encrypted data.

For more information, see the Encryption section of the Rust driver documentation.

## GridFS Rust Support
The 2.4.1 release of the MongoDB Rust driver also (finally!) added support for GridFS, allowing storage and retrieval of files that exceed the BSON document size limit. 

## Tracing Support 
This release had one other noteworthy item in it - the driver now emits tracing events at points of interest. Note that this API is considered unstable as the tracing crate has not reached 1.0 yet; future minor versions of the driver may upgrade the tracing dependency to a new version which is not backwards-compatible with Subscribers that depend on older versions of tracing. You can read more about tracing from the crates.io documentation here.

## Install the MongoDB Rust Driver
To check out these new features, you'll need to install the MongoDB Rust driver, which is available on crates.io. To use the driver in your application, simply add it to your project's Cargo.toml.

```
[dependencies]
mongodb = "2.4.0-beta"
```
# Atlas Search is a Game Changer!

Every four years, for the sake of blending in, I pretend to know soccer (football, for my non-American friends). I smile. I cheer. I pretend to understand what "offsides" means. But what do I know about soccer, anyway? My soccer knowledge is solely defined by my status as a former soccer mom with an addiction to Ted Lasso.

When the massive soccer tournaments are on, I’m overwhelmed by the exhilarated masses. Painted faces to match their colorful soccer jerseys. Jerseys with unfamiliar names from far away places. I recognize Messi and Ronaldo, but the others? Mkhitaryan, Szczęsny, Großkreutz? How can I look up their stats to feign familiarity when I have no idea how to spell their names?

Well, now there’s an app for that. And it’s built with Atlas Search: www.atlassearchsoccer.com. Check out the video tutorial:

:youtube]{vid=1uTmDNTdgaw&t}

**Build your own dream team!** 

With Atlas Search Soccer,  you can scour across 22,000 players to build your own dream team of players across national and club teams. This instance of Atlas Search lets you search on a variety of different parameters and data types. Equipped with only a search box, sliders, and checkboxes, find the world's best players with the most impossible-to-spell names to build out your own dream team. Autocomplete, wildcard, and filters to find Ibrahimović, Błaszczykowski, and Szczęsny? No problem!

When you pick a footballer for your team, he is written to local storage on your device. That way, your team stays warmed up and on the pitch even after you close your browser. You can then compare your dream team with your friends.

**Impress your soccerphile friends!**

Atlas Search Soccer grants you *instant* credibility in sports bars. Who is the best current French player? Who plays goalie for Arsenal? Is Ronaldo from Portugal or Brazil?  You can say with confidence because you have the *DATA!* Atlas Search lets you find it fast!

**Learn all the $search Skills and Drills!**

As you interact with the application, you'll see the $search operator in a MongoDB aggregation pipeline live in-action! Click on the Advanced Scouting image for more options using the compound operator. Learn all the ways and plays to build complex, fine-grained, full-text searches across text, date, and numerics.

* search operators
    * text
    * wildcard
    * autocomplete
    * range
    * moreLikeThis
* fuzzy matching
* indexes and analyzers
* compound operator
* relevance based scoring
* custom score modifiers
* filters, facets and counts

Over the next season, we will launch a series of tutorials, breaking down how to implement all of these features. We can even cover GraphQL and the Data API if we head into extra time. And of course, we will provide tips and tricks for optimal performance.

**Gain a home-field advantage by playing in your own stadium!**

[Here is the repo so you can build Atlas Search Soccer on your own free-forever cluster.

So give it a shot. You'll be an Atlas Search pro in no time!
# Easy Migration: From Relational Database to MongoDB with MongoDB Relational Migrator

Defining the process of data migration from a relational database to MongoDB has always been a complex task. Some have opted for a custom approach, adopting custom solutions such as scripts, whereas others have preferred to use third-party tools. 

It is in this context that the Relational Migrator enters the picture, melting the complexity of this transition from a relational database to MongoDB as naturally as the sun melts the snow.

## How Relational Migrator comes to our help

In the context of a relational database to MongoDB migration project, several questions arise — for example:

- What tool should you use to best perform this migration?
- How can this migration process be made time-optimal for a medium/large size database?
- How will the data need to be modeled on MongoDB?
- How much time/resources will it take to restructure SQL queries to MQL?

Consider the following architecture, as an example:

:

Logstash is a free and open server-side data processing pipeline that ingests data from a multitude of sources, transforms it, and then sends it to your favorite "stash."

This tool effectively achieves the goal by dynamically performing the following operations:

- Ingestion of data from the source — PostgreSQL
- Data transformation — Logstash
- Distribution of the transformed data to the destination — MongoDB

Great! So, it will be possible to migrate data and benefit from high flexibility in its transformation, and we also assume relatively short time frames because we've done some very good tuning, but different pipelines will have to be defined manually. 

Let us concretize with an example what we have been telling ourselves so far by considering the following scheme:

!

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# Mastering Kotlin: Creating an API With Ktor and MongoDB Atlas

Kotlin's simplicity, Java interoperability, and Ktor's user-friendly framework combined with MongoDB Atlas' flexible cloud database provide a robust stack for modern software development.

Together, we'll demonstrate and set up the Ktor project, implement CRUD operations, define API route endpoints, and run the application. By the end, you'll have a solid understanding of Kotlin's capabilities in API development and the tools needed to succeed in modern software development.

## Demonstration

.

.

Once your account is created, access the **Overview** menu, then **Connect**, and select **Kotlin**. After that, our connection **string** will be available as shown in the image below:

Any questions? Come chat with us in the MongoDB Developer Community. 

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# Introducing Atlas Stream Processing Support Within the MongoDB for VS Code Extension

Across industries, teams are building applications that need access to low-latency data to deliver compelling experiences and gain valuable business insights. Stream processing is a fundamental building block powering these applications. Stream processing lets developers discover and act on streaming data (data in motion), and combine that data when necessary with data at rest (data stored in a database). MongoDB is a natural fit for streaming data with its capabilities around storing and querying unstructured data and an effective query API. MongoDB Atlas Stream Processing is a service within MongoDB Atlas that provides native stream processing capabilities. In this article, you will learn how to use the MongoDB for VS Code extension to create and manage stream processors in MongoDB Atlas.

## Installation

MongoDB support for VS Code is provided by the MongoDB for VS Code extension. To install the MongoDB for VS Code extension, launch VS Code, open the Extensions view, and search for MongoDB to filter the results. Select the MongoDB for VS Code extension.

 or visit the online documentation.

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# Laravel MongoDB 4.2 Released, With Laravel 11 Support

The PHP team is happy to announce that version 4.2 of the Laravel MongoDB integration is now available!

## Highlights

**Laravel 11 support**

The MongoDB Laravel integration now supports Laravel 11, ensuring compatibility with the latest framework version and enabling developers to leverage its new features and enhancements. To apply transformation on model attributes, the new recommended way is to declare the Model::casts method.

**Fixed transaction issue with firstOrCreate()**

Previously, using firstOrCreate() in a transaction would result in an error. This problem has been resolved by implementing the underlying Model::createOrFirst() method with the atomic operation findOneAndUpdate.

**Support for whereAll and whereAny**

The library now supports the new methods whereAll and whereAny, introduced in Laravel 10.47.

## Installation

This library may be installed or upgraded with:

```
composer require mongodb/laravel-mongodb:4.2.0
```

## Resources

Documentation and other resources to get you started with Laravel and MongoDB databases are shared below:

- Laravel MongoDB documentation
- Quick Start with MongoDB and Laravel
- Release notes 

Give it a try today and let us know what you think! Please report any ideas, bugs, or feedback in the GitHub repository or the PHPORM Jira project, as we continue to improve and enhance the integration.
# SymfonyLive Berlin 2024

Come and meet our team at SymfonyLive Berlin!

## Sessions
Don't miss these talks by our team:

|Date| Titre| Speaker|
|---|---|---|
|June 20th|From Pickles to Pie: Sweeten Your PHP Extension Installs|Andreas Braun|

## Additional Resources
Dive deeper in your MongoDB exploration with the following resources:
* Tutorial MongoDB + Symfony
* Tutorial MongoDB + Doctrine
# Spring I/O 2024

Come and meet our team at Spring I/O!

## Sessions
Don't miss these talks by our team:

|Date| Titre| Speaker|
|---|---|---|
| May 30th | MongoDB Sprout: Where Data Meets Spring | Tim Kelly |

## Additional Resources
Dive deeper in your MongoDB exploration with the following resources:
Check out how to add Vector Search to your Java Spring Boot application in this tutorial.

Integrating Spring Boot, Reactive, Spring Data, and MongoDB can be a challenge, especially if you are just starting out. Check out this code example to get started right away!

Need to deploy an application on K8s that connects to MongoDB Atlas? This tutorial will take you through the steps you need to get started in no time.
# CppCon 2024

Come and meet our team at CppCon!

## Sessions
Don't miss these talks by our team:

|Date| Titre| Speaker|
|---|---|---|
|September 21st and 22nd|Workshop: C++ Testing like a Ninja for Novice Testers|Jorge Ortiz & Rishabh Bisht|

## Additional Resources

We will publish a repository with all of the code for the workshop, so remember to visit this page again and check if it is available.

Dive deeper in your MongoDB exploration with the following resources:
- MongoDB Resources for Cpp developers
# Developer Day Melbourne

Welcome to MongoDB Developer Day Melbourne! Below you can find all the resources you will need for the day.

## Data Modeling and Design Patterns
* Slides
* Library application
* System requirements

## MongoDB Atlas Setup: Hands-on exercises setup and troubleshooting
* Intro lab: hands-on exercises
* Data import tool

## Aggregation Pipelines Lab
* Slides
* Aggregations lab: hands-on exercises

## Search Lab
* Slides
* Search lab: hands-on exercises

## Additional resources
* Library management system code
* MongoDB data modeling book
* Data Modeling course on MongoDB University
* MongoDB for SQL Pros on MongoDB University
* Atlas Search Workshop: An in-depth workshop that uses the more advanced features of Atlas Search

## How was it?
Let us know what you liked about this day, and how we can improve (and get a cool 🧦 gift 🧦) by filling out this survey.

## Join the Community
Stay connected, and join our community:
* Join the Melbourne MongoDB User Group!
* Sign up for the MongoDB Community Forums.
# Developer Day Sydney

Welcome to MongoDB Developer Day Sydney! Below you can find all the resources you will need for the day.

## Data Modeling and Design Patterns
* Slides
* Library application
* System requirements

## MongoDB Atlas Setup: Hands-on exercises setup and troubleshooting
* Intro lab: hands-on exercises
* Data import tool

## Aggregation Pipelines Lab
* Slides
* Aggregations lab: hands-on exercises

## Search Lab
* Slides
* Search lab: hands-on exercises

## Additional resources
* Library management system code
* MongoDB data modeling book
* Data Modeling course on MongoDB University
* MongoDB for SQL Pros on MongoDB University
* Atlas Search Workshop: An in-depth workshop that uses the more advanced features of Atlas Search

## How was it?
Let us know what you liked about this day, and how we can improve (and get a cool 🧦 gift 🧦) by filling out this survey.

## Join the Community
Stay connected, and join our community:
* Join the Sydney MongoDB User Group!
* Sign up for the MongoDB Community Forums.
# Developer Day Auckland

Welcome to MongoDB Developer Day Auckland! Below you can find all the resources you will need for the day.

## Data Modeling and Design Patterns
* Slides
* Library application
* System requirements

## MongoDB Atlas Setup: Hands-on exercises setup and troubleshooting
* Intro lab: hands-on exercises
* Data import tool

## Aggregation Pipelines Lab
* Slides
* Aggregations lab: hands-on exercises

## Search Lab
* Slides
* Search lab: hands-on exercises

## Additional resources
* Library management system code
* MongoDB data modeling book
* Data Modeling course on MongoDB University
* MongoDB for SQL Pros on MongoDB University
* Atlas Search Workshop: An in-depth workshop that uses the more advanced features of Atlas Search

## How was it?
Let us know what you liked about this day, and how we can improve by filling out this survey.

## Join the Community
Stay connected, and join our community:
* Join the Auckland MongoDB User Group!
* Sign up for the MongoDB Community Forums.
# Deprecating MongoDB Atlas GraphQL and Hosting Services

As part of MongoDB’s ongoing commitment to innovation and providing the best possible developer experience, we have some important updates about our Atlas GraphQL and Atlas Hosting services. Our goal is always to offer developers the best services and tools on Atlas, whether built by MongoDB or delivered by our trusted partners so that builders can focus on providing the best application possible. In line with this vision, we strategically decided to deprecate the Atlas GraphQL API and Atlas Hosting services. 

This blog post outlines what this means for users, the timeline for this transition, and how we plan to support you through this change.

**What’s Changing?**

New users cannot create apps with GraphQL / hosting enabled. Existing customers will have time to move off of the service and find an alternative solution by **March 12, 2025**.

**Why Are We Making This Change?**

The decision to streamline our services reflects our commitment to natively offering best-in-class services while collaborating with leading partners to provide the most comprehensive developer data platform.

**How We’re Supporting You**

We recognize that challenges can come with change, so our team will continue to provide comprehensive assistance and guidance to ensure a smooth migration process. As part of our commitment to providing developers the best services and tools, we have identified several MongoDB partners who offer best-in-class solutions with similar functionality to our GraphQL and hosting services.

We’ve collaborated with some of these partners to create official step by step migration guides in order to provide a seamless transition to our customers. We encourage you to explore these options here.

- **Migration Assistance**: Learn more about the MongoDB partner integrations that make it easy to connect to your Atlas database:
    - **GraphQL Partners**: Apollo, Hasura, WunderGraph, Grafbase, AWS AppSync
    - **Hosting Partners**: Vercel, Netlify, Koyeb, Northflank, DigitalOcean
- **Support and Guidance**: Our support team is available to assist you with any questions or concerns. We encourage you to reach out via the MongoDB Support Portal or contact your Account Executive for personalized assistance.

**Looking Forward**

We’re here to support you every step of the way as you explore and migrate to alternative solutions. Our team is working diligently to ensure this transition is as seamless as possible for all affected users. We’re also excited about what the future holds for the MongoDB Atlas, the industry’s leading developer data platform, and the new features we’re developing to enhance your experience.
# Developer Day Singapore

Welcome to MongoDB Developer Day! Below you can find all the resources you will need for the day.

## Data Modeling and Design Patterns

* Slides
* Library application
* System requirements

### Hands-on exercises setup and troubleshooting
* Self-paced content -- Atlas cluster creation and loading sample data.
* Data import tool
* If CodeSpaces doesn't work, try downloading the code.
* Import tool not working? Try downloading the dataset, and ask an instructor for help on importing the data.

### Additional resources
* Library management system code
* MongoDB data modeling book
* Data Modeling course on MongoDB University
* MongoDB for SQL Pros on MongoDB University

## Aggregation Pipelines Lab
* Aggregations hands-on exercises
* Slides

## Search Lab
* Slides
* Search lab hands-on content

### Dive deeper
Do you want to learn more about Atlas Search? Check these out.
* Atlas Search Workshop: An in-depth workshop that uses the more advanced features of Atlas Search
# MongoDB Day with Kementerian Kesehatan

Welcome to MongoDB Developer Day! Below you can find all the resources you will need for the day.

## Data Modeling and Design Patterns

* Slides
* Library application
* System requirements

### Hands-on exercises setup and troubleshooting
* Self-paced content -- Atlas cluster creation and loading sample data.
* Data import tool
* If CodeSpaces doesn't work, try downloading the code.
* Import tool not working? Try downloading the dataset, and ask an instructor for help on importing the data.

### Additional resources
* Library management system code
* MongoDB data modeling book
* Data Modeling course on MongoDB University
* MongoDB for SQL Pros on MongoDB University

## Aggregation Pipelines Lab
* Aggregations hands-on exercises
* Slides

## Search Lab
* Slides
* Search lab hands-on content

### Dive deeper
Do you want to learn more about Atlas Search? Check these out.
* Atlas Search Workshop: An in-depth workshop that uses the more advanced features of Atlas Search