What We're Reading This Week

MongoDB
February 6, 2014 | Updated: July 5, 2016
#Company

Here’s what we’re reading this week from the MongoDB community.

ScaleGrid: Which is the Best MongoDB GUI?

MongoHQ: At the MongoDB 2.6 Index Intersection

Mongo Lab: Finding and Terminating Long-Running Operations in MongoDB

Code Hero: Node.js y Express: Aplicación con MongoDB Parte II

Mongo HQ: Redis, MongoDB, and the Power of Incremency

The MongoDB Blog: Meet Daniel Gottlieb, MMS Backup Engineer

The MongoDB Blog: Looking Beyond Labels Like Relational and NoSQL

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Looking beyond labels like relational and NoSQL

According to a new Dice.com salary survey , MongoDB ranks as one of top-10 most highly compensated technology skills. Indeed.com rates MongoDB as the second hottest job trend. And DB-Engines.com, which ranks over 200 databases on their relative popularity, MongoDB is now the fifth-most popular database in the world, this month surpassing IBM's DB2. All great, right? Maybe. Buried in the Dice.com data, as well as the Indeed.com data, is evidence of real confusion. For example, of the top-10 most highly compensated skills in Dice.com's survey is "NoSQL ." NoSQL is not a technology. It's not really something a developer can "know" in any real sense. NoSQL is a movement that describes a different way of modeling data but, as Basho founder Justin Sheehy correctly noted , there are as many differences among so-called NoSQL databases as there are similarities. As such, knowing Basho's Riak won't really help you understand MongoDB. Perhaps at a high, conceptual level, but expertise in one doesn't really translate into familiarity with another. They are different databases with different approaches. Employers looking for generic NoSQL skills need to think more deeply about what their application requirements are. Looking beyond relational databases for modern application requirements is a good start, but looking to generic "NoSQL" is not sufficient. Organizations should be looking for a modern database that dramatically improves developer productivity, encourages application iteration and enables a new wave of transformational applications in areas like Big Data , Internet of Things , mobile and more . That database is MongoDB. Is MongoDB "NoSQL." Sure. But it's much bigger than that ( based on what people search for on Google , many organizations already seem to understand this). MongoDB is the fastest-growing database in the world , not because it fits the NoSQL category, but because it significantly improves the productivity of developers and the organizations for which they work. So if you're looking to hire technology talent, you're far more likely to be successful hiring an experienced MongoDB engineer than a "NoSQL engineer." MongoDB, after all, is an actual database. NoSQL simply describes an important movement.

February 4, 2014
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Collaborating to Build AI Apps: MongoDB and Partners at Google Cloud Next '24

From April 9 to April 11, Las Vegas became the center of the tech world, as Google Cloud Next '24 took over the Mandalay Bay Convention Center—and the convention’s spotlight shined brightest on gen AI. Check out our AI resource page to learn more about building AI-powered apps with MongoDB. Between MongoDB’s big announcements with Google Cloud (which included an expanded collaboration to enhance building, scaling, and deploying GenAI applications using MongoDB Atlas Vector Search and Vertex AI ), industry sessions, and customer meetings, we offered in-booth lightning talks with leaders from four MongoDB partners—LangChain, LlamaIndex, Patronus AI, and Unstructured—who shared valuable insights and best practices with developers who want to embed AI into their existing applications or build new-generation apps powered by AI. Developing next-generation AI applications involves several challenges, including handling complex data sources, incorporating structured and unstructured data, and mitigating scalability and performance issues in processing and analyzing them. The lightning talks at Google Cloud Next ‘24 addressed some of these critical topics and presented practical solutions. One of the most popular sessions was from Harrison Chase , co-founder and CEO at LangChain , an open-source framework for building applications based on large language models (LLMs). Harrison provided tips on fixing your retrieval-augmented generation (RAG) pipeline when it fails, addressing the most common pitfalls of fact retrieval, non-semantic components, conflicting information, and other failure modes. Harrison recommended developers use LangChain templates for MongoDB Atlas to deploy RAG applications quickly. Meanwhile, LlamaIndex —an orchestration framework that integrates private and public data for building applications using LLMs—was represented by Simon Suo , co-founder and CTO, who discussed the complexities of advanced document RAG and the importance of using good data to perform better retrieval and parsing. He also highlighted MongoDB’s partnership with LlamaIndex, allowing for ingesting data into the MongoDB Atlas Vector database and retrieving the index from MongoDB Atlas via LlamaParse and LlamaCloud . Guillaume Nozière - Patronus AI Andrew Zane - Unstructured Amidst so many booths, activities, and competing programming, a range of developers from across industries showed up to these insightful sessions, where they could engage with experts, ask questions, and network in a casual setting. They also learned how our AI partners and MongoDB work together to offer complementary solutions to create a seamless gen AI development experience. We are grateful for LangChain, LlamaIndex, Patronus AI, and Unstructured's ongoing partnership. We look forward to expanding our collaboration to help our joint customers build the next generation of AI applications. To learn more about building AI-powered apps with MongoDB, check out our AI Resources Hub and stop by our Partner Ecosystem Catalog to read about our integrations with these and other AI partners.

April 23, 2024