The MongoDB Podcast

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The MongoDB Podcast features guest interviews including developers, startups, and founders with MongoDB Principal Developer Advocate Michael Lynn. Learn about new and emerging technology, how to use the various MongoDB products and best practices, how organizations are using MongoDB, and what lead them to choose MongoDB over other databases.

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Recent Hosts, Guests & Topics

Here's a quick summary of the last 5 episodes on The MongoDB Podcast.

Hosts

Shane McAllister Jesse Hall Michael Lynn

Previous Guests

Peter Ngai
Peter Ngai is the Principal Architect at SnapLogic, where he specializes in data integration and management solutions. With extensive experience in cloud technologies and data architecture, Peter has been instrumental in developing strategies that help organizations navigate complex multi-cloud environments. His expertise includes leveraging low-code and no-code platforms to simplify data connectivity and enhance business automation. Peter is known for his insights into AI-driven data automation and compliance with data security regulations.
Sachin Hejip
Sachin Hejip is a professional associated with Dataworkz, where he focuses on developing innovative solutions that leverage MongoDB technologies. He has expertise in building applications that utilize natural language processing and AI to enhance data management and customer experiences. His work includes the creation of the Dataworkz Agent Builder, which simplifies the development of Agentic RAG applications.
Tomer Shalev
Tomer Shalev is the creator of Storecraft, an open-source commerce platform that integrates with MongoDB to provide scalable solutions for e-commerce. He has a background in software development and is known for his work in building modular and future-proof commerce solutions that leverage AI and advanced data management techniques.
Shane McAllister
Shane McAllister is a technology expert and advocate for MongoDB, known for his work in the field of database management and application development. He has extensive experience in implementing MongoDB solutions for various organizations, focusing on enhancing performance and scalability in data-driven applications.
Nenad
Nenad is a MongoDB Champion recognized for his contributions to the MongoDB community. He specializes in database architecture and optimization, particularly in the context of AI and machine learning applications. His expertise includes semantic search technologies and their implementation in real-world scenarios.

Topics Discussed

Data Integration Multi-Cloud Hybrid Cloud Edge Computing SnapLogic MongoDB AI Artificial Intelligence Data Automation iPaaS Low-Code No-Code Data Architecture Data Management Cloud Data Enterprise Data API Integration Data Compliance Data Sovereignty Data Security Business Automation ETL ELT Tech Stack Simplification Natural Language MongoDB Atlas Vector Search Agent Builder Large Language Models RAG applications unstructured data Dataworkz semantic search data management Vector Search Atlas Vector Search Unstructured Data RAG Semantic Search Langchain Llama Index Big Data AI-driven workflows open-source commerce platform vector search dynamic pricing email automation custom discount logic OpenAI-powered product recommendations AI-Powered Image Search semantic image search MongoDB Atlas image vectors embedding models optimizing indexes AI/ML workloads

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Episodes

Here's the recent few episodes on The MongoDB Podcast.

0:00 58:31

EP. 264 Beyond the Database: Mastering Multi-Cloud Data, AI Automation & Integration (feat. Peter Ngai, SnapLogic)

Hosts
Shane McAllister
Guests
Peter Ngai
Keywords
Data Integration Multi-Cloud Hybrid Cloud Edge Computing SnapLogic MongoDB AI Artificial Intelligence Data Automation iPaaS Low-Code No-Code Data Architecture Data Management Cloud Data Enterprise Data API Integration Data Compliance Data Sovereignty Data Security Business Automation ETL ELT Tech Stack Simplification

Heads up! This episode features a demonstration of the SnapLogic UI and its AI Agent Creator towards the end. For the full visual experience, check out the video version on the Spotify app! ✨


(Episode Summary)Tired of tangled data spread across multiple clouds, on-premise systems, and the edge? In this episode, MongoDB's Shane McAllister sits down with Peter Ngai, Principal Architect at SnapLogic, to explore the future of data integration and management in today's complex tech landscape.

Dive into the challenges and solutions surrounding modern data architecture, including:

  • Navigating the complexities of multi-cloud and hybrid cloud environments.
  • The secrets to building flexible, resilient data ecosystems that avoid vendor lock-in.
  • Strategies for seamless data integration and connecting disparate applications using low-code/no-code platforms like SnapLogic.
  • Meeting critical data compliance, security, and sovereignty demands (think GDPR, HIPAA, etc.).
  • How AI is revolutionizing data automation and providing faster access to insights (featuring SnapLogic's Agent Creator).
  • The powerful synergy between SnapLogic and MongoDB, leveraging MongoDB both internally and for customer integrations.
  • Real-world applications, from IoT data processing to simplifying enterprise workflows.

Whether you're an IT leader, data engineer, business analyst, or simply curious about cloud strategy, iPaaS solutions, AI in business, or simplifying your data stack, Peter offers invaluable insights into making data connectivity a driver, not a barrier, for innovation.

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Keywords: Data Integration, Multi-Cloud, Hybrid Cloud, Edge Computing, SnapLogic, MongoDB, AI, Artificial Intelligence, Data Automation, iPaaS, Low-Code, No-Code, Data Architecture, Data Management, Cloud Data, Enterprise Data, API Integration, Data Compliance, Data Sovereignty, Data Security, Business Automation, ETL, ELT, Tech Stack Simplification, Peter Ngai, Shane McAllister.

0:00 1:11:04

EP. 263 Building Agents with Natural Language with guest

Hosts
Shane McAllister
Guests
Sachin Hejip
Keywords
Natural Language MongoDB Atlas Vector Search Agent Builder AI Large Language Models RAG applications unstructured data Dataworkz semantic search data management

**(Note: Spotify listeners can also watch the screen sharing video accompanying the audio. Other podcast platforms offer the audio-only version.)**

In this episode of MongoDB Podcast Live, host Shane McAllister is joined by Sachin Hejip from Dataworkz. Sachin will showcase “Dataworkz Agent Builder” which is built with MongoDB Atlas Vector Search, and demonstrate how it can use Natural Language to create Agents and in turn, automate and simplify the creation of Agentic RAG applications. Sachin will demo the MongoDB Leafy Portal Chatbot Agent, which combines operational data with unstructured data for personalised customer experience and support, built using Dataworkz and MongoDB.

Struggling with millions of unstructured documents, legacy records, or scattered data formats? Discover how AI, Large Language Models (LLMs), and MongoDB are revolutionizing data management in this episode of the MongoDB Podcast.Join host Shane McAllister and the team as they delve into tackling complex data challenges using cutting-edge technology. Learn how MongoDB Atlas Vector Search enables powerful semantic search and Retrieval Augmented Generation (RAG) applications, transforming chaotic information into valuable insights. Explore integrations with popular frameworks like Langchain and Llama Index.Find out how to efficiently process and make sense of your unstructured data, potentially saving significant costs and unlocking new possibilities.Ready to dive deeper?

#MongoDB #AI #LLM #LargeLanguageModels #VectorSearch #AtlasVectorSearch #UnstructuredData #Podcast #DataManagement #Dataworkz #Observability #Developer #BigData #RAG

0:00 56:30

EP. 262 Solving Unstructured Data Challenges with AI & Vector Search

Hosts
Shane McAllister
Keywords
AI Large Language Models MongoDB Vector Search Atlas Vector Search Unstructured Data Data Management RAG Semantic Search Langchain Llama Index Big Data

**(Note: Spotify listeners can also watch the screen sharing video accompanying the audio. Other podcast platforms offer the audio-only version.)**


Struggling with millions of unstructured documents, legacy records, or scattered data formats? Discover how AI, Large Language Models (LLMs), and MongoDB are revolutionizing data management in this episode of the MongoDB Podcast.Join host Shane McAllister and the team as they delve into tackling complex data challenges using cutting-edge technology. Learn how MongoDB Atlas Vector Search enables powerful semantic search and Retrieval Augmented Generation (RAG) applications, transforming chaotic information into valuable insights. Explore integrations with popular frameworks like Langchain and Llama Index.Find out how to efficiently process and make sense of your unstructured data, potentially saving significant costs and unlocking new possibilities.Ready to dive deeper?#MongoDB #AI #LLM #LargeLanguageModels #VectorSearch #AtlasVectorSearch #UnstructuredData #Podcast #DataManagement #RAG #SemanticSearch #Langchain #LlamaIndex #Developer #BigData

0:00 1:00:22

EP.261 Building Next-Gen AI E-Commerce with Storecraft & MongoDB | Live Code Demo

Hosts
Jesse Hall
Guests
Tomer Shalev
Keywords
AI-driven workflows open-source commerce platform MongoDB vector search dynamic pricing email automation custom discount logic OpenAI-powered product recommendations

MongoDB staff developer advocate Jesse Hall teams up with Storecraft creator Tomer Shalev to dissect how this open-source commerce platform leverages MongoDB for scalable, AI-driven workflows. Watch them live-code integrations (vector search, dynamic pricing, email automation) and explore real-world use cases—from custom discount logic to OpenAI-powered product recommendations.

Perfect for developers building modular, future-proof commerce solutions.

0:00 57:33

EP.260 Vector Search Secrets Revealed! - AI-Powered Image Search with MongoDB - Live Demo

Hosts
Michael Lynn
Guests
Shane McAllister Nenad
Keywords
Vector Search AI-Powered Image Search semantic image search MongoDB Atlas image vectors embedding models optimizing indexes AI/ML workloads

Ever wondered how companies like Amazon or Pinterest deliver lightning-fast image search? Dive into this episode of MongoDB Podcast Live with Shane McAllister and Nenad, a MongoDB Champion, as they unravel the magic of semantic image search powered by MongoDB Atlas Vector Search!

🔍 What You’ll Learn:

  • Why semantic search is a game-changer for AI-driven applications (spoiler: it’s all about meaning, not just keywords!).

  • How to transform images into vectors (embeddings) and store them alongside your data—no clunky ETL pipelines required!

  • live demo showcasing real-time image search on a 40,000+ product dataset (spoiler #2: it’s blazing fast and shockingly simple to build!).

  • Pro tips on choosing embedding models, optimizing indexes, and avoiding common pitfalls.

  • Why MongoDB’s unified data model crushes traditional databases for AI/ML workloads.


    👥 For Developers & Data Engineers:
    Whether you’re a JavaScript, AI enthusiast, or just tired of JOINs, this episode is your roadmap to building smarter, faster apps. Plus, learn why companies like Toyota and Verizon trust MongoDB for mission-critical AI workloads.

Ratings

Global:
4.9 rating 91 reviews

USA

4.9 ratings 72 reviews

Ireland

5.0 ratings 11 reviews

UK

4.3 ratings 6 reviews

Australia

5.0 ratings 1 reviews

New Zealand

5.0 ratings 1 reviews

Canada

0.0 ratings 0 reviews

Singapore

0.0 ratings 0 reviews

South Africa

0.0 ratings 0 reviews