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Anywhere Real Estate, a leader in integrated residential real estate services with a brand portfolio spanning some of the most recognized names in real estate: Better Homes and Gardens Real Estate, CENTURY 21, Coldwell Banker, and Sotheby's International Realty, will share why and how they are using MongoDB Atlas to drive digital transformation across their business and the role MongoDB Atlas Search plays in simplifying the back-end that lets millions of home buyers across the country discover their dream home, and how they're evaluating the use of Atlas Vector Search and LLMs to take this home search experience to a new level.
Learn how MongoDB is helping Anywhere to iterate and innovate quickly and stay ahead of this highly competitive and evolving real estate market, as well as what they plan to do next with MongoDB. In this MongoDB video, we'll explore the journey of Anywhere Real Estate in adopting MongoDB Atlas and MongoDB Atlas Search. We'll delve into the technical decisions, performance evaluations, and the overall experience of integrating MongoDB's solutions into their real estate platform. This session is packed with insights on how MongoDB Atlas has been leveraged to meet business and engineering goals, providing a modern tech stack, fast response times, and low operational overhead.
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⏱️ Timestamps ⏱️
Introduction and Company Background [00:00:00 - 00:04:55]
The speaker introduces the day's topic and provides background information on Anywhere Real Estate, mentioning the various brands under the company's umbrella and the significance of the company in the real estate market.
Website Complexity and Search Goals [00:04:55 - 00:09:47]
An explanation of the complexities involved in a real estate search website is provided, detailing the types of searches, filters, and the expectations for fast performance. The speaker also outlines the business and engineering goals for their centralized search capability.
Choosing MongoDB Atlas [00:09:47 - 00:14:47]
The journey of adopting MongoDB Atlas is discussed, including the initial use cases, the benefits of a schema-less system, and the operational advantages that led to the selection of MongoDB Atlas over other databases.
Implementing Atlas Search [00:14:47 - 00:19:53]
The speaker shares the process of implementing Atlas Search, including performance testing, the challenges faced, and the solutions provided by MongoDB's partnership. The importance of dedicated search nodes and the use of Professional Services are highlighted.
Engineering Observations and Future Plans [00:19:53 - 00:24:55]
The speaker reflects on the stability and performance of the system since implementing Atlas Search and shares future plans, including the use of dedicated search nodes and exploring Vector DB for enhanced search capabilities.
Q&A Session [00:24:55 - 00:29:34]
The session concludes with a Q&A segment where the speaker addresses questions about data storage strategies, the comparison with other search solutions like ElasticSearch, and the use of MongoDB for AI and machine learning applications.
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