Search
Attendance Type
Event Type
Language
Technology
Content Type
Products
Expertise Level
Contributed By
Example Type
- Latest
- Highest Rated
All Content
Video
Intro to Atlas Search
Note: Questions can only be asked through the Zoom Webinar, sign up here → https://trymongodb.com/3E6yygC Subscribe to MongoDB YouTube→ https://mdb.link/subscribe Atlas Search combines the power of Apache Lucene - the technology behind the world’s most popular search engines - with the developer productivity, scale, and resilience of MongoDB Atlas to make it easier than ever to integrate fast, relevance-based search capabilities into all of your MongoDB applications. Join us for our Intro to MongoDB Atlas Search webinar where, with a few clicks and keystrokes, we will unravel the mystery behind the search bar. We’ll search through different data types, including text, numbers, dates, and geoJSON while exploring a variety of search capabilities MongoDB University Course: Atlas Search → https://trymongodb.com/3E9gTow The Atlas Search 'cene: Season 1 → https://trymongodb.com/40z0um8 Visit Mongodb.com → https://trymongodb.com/4hhuxV3 Read the MongoDB Blog → https://trymongodb.com/4akMqA7 Check out the MongoDB Developer Center → https://trymongodb.com/3Wnr6Eb
Feb 26, 2025
Video
Power-Up Your Queries: MongoDB's Aggregation Framework (C# / .NET)
Note: Questions can only be asked through the Zoom Webinar, sign up here → https://trymongodb.com/4fYlc3y Subscribe to MongoDB YouTube→ https://mdb.link/subscribe In this webinar, we'll show you how MongoDB's aggregation framework allows you to write simple, and then increasingly complex, queries and aggregations against your datasets, helping you group, join, limit, skip, and bucket across documents in your collections. MongoDB University: Advanced Queries and Data Processing → https://trymongodb.com/3DSCvFU Visit Mongodb.com → https://trymongodb.com/4gV2Vp4 Read the MongoDB Blog → https://trymongodb.com/3WlBU61 Check out the MongoDB Developer Center → https://trymongodb.com/40AzNOb
Feb 19, 2025
Video
Intro to Data Modeling
Note: Questions can only be asked through the Zoom Webinar, sign up here → https://trymongodb.com/3CbYbwc Subscribe to MongoDB YouTube→ https://mdb.link/subscribe A frequently asked question in the MongoDB community is “I’m designing an application to do X, how do I model the data?” In this webinar, we will examine the most important considerations when making decisions about your data model, so that you can create the model that best fits your application. You will learn: The differences between data modeling in MongoDB vs. relational databases The key considerations for data modeling with MongoDB How to further enhance the power of the document model with schema design patterns Intro to Data Modeling Docs → https://trymongodb.com/42yL6rF Data Modeling Explained → https://trymongodb.com/3PDnV7S Visit Mongodb.com → https://trymongodb.com/40jebV3 Read the MongoDB Blog → https://trymongodb.com/3PIJKCF Check out the MongoDB Developer Center → https://trymongodb.com/4gYKC2m
Feb 12, 2025
Video
Intro to MongoDB
Note: Questions can only be asked through the Zoom Webinar, sign up here → https://trymongodb.com/3PC1yQ8 Subscribe to MongoDB YouTube→ https://mdb.link/subscribe Senior Developer Advocate Jesse Hall will showcase the unique advantages of the document data model and show you how to deploy an Atlas cluster. Jesse will present a demo of how to get started with MongoDB Atlas and walk you through how to: Create your first cluster, add an IP address and set up a database user Load sample data using a Next.js e-commerce demo app Connect to the database Intro to MongoDB Docs → https://trymongodb.com/40zXTZi Visit Mongodb.com → https://trymongodb.com/42yKrXd Read the MongoDB Blog → https://trymongodb.com/4g3Lbq6 Check out the MongoDB Developer Center → https://trymongodb.com/42fJLpf
Feb 05, 2025
Video
What is an Embedding? | MongoDB #ai #embeddingmodel
Why do so many people suddenly care about embeddings, a concept that has existed since the 1950s? Let's talk about what embeddings are and how embedding models work. Learn more on Developer Center: https://mdb.link/embedding-model
Jan 23, 2025
Tutorial
Building a Dynamic Pricing Microservice with Vertex AI and MongoDB Atlas
Utilizing MongoDB Atlas for efficient data storage and Google Cloud Platform for complex calculations and hosting, businesses can implement real-time pricing adjustments based on customer behavior and competitor data.
Jan 22, 2025
(+1)
Video
Building a Semantic Search Application with MongoDB and Quarkus using Vector Search
✅ Try MongoDB 8.0 → https://mdb.link/91SzYGDmFoI ✅ Sign-up for a free cluster → https://mdb.link/91SzYGDmFoI-try ✅ Article link → https://mdb.link/91SzYGDmFoI-read - Discover how to harness the power of MongoDB's vector search capability to build a semantic search application using the Quarkus framework. In this comprehensive tutorial, we'll guide you step-by-step from understanding vector search fundamentals to implementing a functional Java application. Learn how to use Gemini AI for vector embeddings, create optimized queries, and set up your MongoDB Atlas cluster for seamless integration. Whether you're new to vector search or looking to enhance your generative AI applications, this video provides all the tools you need to get started. - 📚 Git repo: https://github.com/mongodb-developer/mongodb-vector-search-with-quarkus Resources: 📚 Vector Embeddings: https://mdb.link/91SzYGDmFoI-models 📚 Gemini AI: https://ai.google.dev/api?lang=python https://ai.google.dev/gemini-api/docs/api-key Similarity values: 📚 Euclidean: https://en.wikipedia.org/wiki/Euclidean_distance 📚 Cosine: https://en.wikipedia.org/wiki/Cosine_similarity 📚 Dot Product: https://en.wikipedia.org/wiki/Dot_product
Jan 21, 2025
Tutorial
Java Faceted Full-Text Search API using MongoDB Atlas Search
This is going to be a fun, practical tutorial demonstrating how to build a Java faceted full-text search API (like the ones powering sites like Amazon)! We’ll use an interesting dataset which showcases how you can effectively pair machine learning/AI-generated data with more traditional search to produce fast, cheap, repeatable, and intuitive search engines.
Jan 17, 2025
LT