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MongoDB

MongoDB

Software Development

New York, NY 874,977 followers

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About us

Headquartered in New York, MongoDB's mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. Built by developers, for developers, our modern database platform is a database with an integrated set of related services that allow development teams to address the growing requirements for today's wide variety of modern applications, all in a unified and consistent user experience. MongoDB has tens of thousands of customers in over 100 countries. The MongoDB database platform has been downloaded hundreds of millions of times since 2007, and there have been millions of builders trained through MongoDB University courses. To learn more, visit mongodb.com.

Website
http://www.mongodb.com
Industry
Software Development
Company size
5,001-10,000 employees
Headquarters
New York, NY
Type
Public Company
Founded
2007
Specialties
open source, databases, mongodb, and software developer

Products

Click here to view MongoDB MongoDB
Click here to view MongoDB

Click here to view MongoDB MongoDB

NoSQL Database Software

MongoDB’s modern database platform integrates all of the data services you need to build modern applications in a unified developer experience. It handles transactional workloads, app-driven analytics, full-text search, AI-enhanced experiences, stream data processing, and more, all while reducing data infrastructure sprawl and complexity.

Locations

  • Primary

    1633 Broadway

    38th Floor

    New York, NY 10019, US

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  • 100 Forrest Avenue

    Palo Alto, California 94301, US

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  • 16 Hatfields

    3rd Floor

    London , UK SE1 8DJ, GB

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  • 3 Shelbourne Building, Crampton Avenue, Ballsbridge

    3rd Floor

    Dublin, Ireland 4, IE

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  • Level 7

    Chinatown Centre 405 Sussex Street, Haymarket

    NSW, NSW 2000, AU

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  • Building No. 10 C, DLF Cyber City, Phase II

    14th Floor

    Gurgaon, Haryana 122002, IN

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  • 8614 Westwood Center Drive

    Suite #705

    Vienna, VA 22182, US

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  • 3340 Peachtree Rd. NE

    Suite 1800

    Atlanta, GA 30326, US

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  • 377 E Butterfield Road

    Suite 260

    Lombard, IL 60148, US

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  • 3711 S. Mopac Expressway

    Building 1, Suite 200

    Austin, TX 78746, US

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  • 5851 Legacy Circle

    6th Floor

    Plano, TX 75024, US

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  • Lincoln Square

    10400 NE 4th St

    Bellevue, WA 98004, US

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  • 1601 Market St.

    Philadelphia, Philadelphia 19103, US

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  • 100 Summit Drive

    Burlington, MA 01803, US

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  • 495 Av. Javier Barros Sierra

    Santa Fe, Mexico City, Distrito Federal 01376, MX

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  • 219 Dufferin St

    Suite #303B

    Toronto, Ontario M6K 3J1, CA

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  • 660 York Street

    San Francisco, CA 94110, US

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  • Spacesworks

    4th floor Barbara Strozzilaan 101

    Amsterdam, Netherlands 1083 HN , NL

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  • Via Pietro Paleocapa 7

    5th floor, Suite 501 - 504

    Milan, Milan 20121, IT

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  • 20 Rue Quentin Bauchart

    Level 2

    Paris, Paris 75008, FR

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  • WeWork Goetheplatz

    Neue Rothofstraße 13-19

    Frankfurt am Main, Frankfurt 60313 , DE

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  • We Work

    Kurfürstendamm 11

    Berlin, Berlin 10719, DE

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  • Design Offices, München Highlight Tower

    Mies-van-der-Rohe-Straße 8

    Munich, Munich D-80807, DE

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  • 144 Menachem Begin Road

    Wework, 34th Floor

    Tel Aviv, Tel Aviv 6492102, IL

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  • Av. de Europa 19

    Alcobendas

    Madrid, Spain 28108, ES

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  • MongoDB c/o Spaces

    Lvl 2, 161 Collins Street

    Melbourne, Melbourne 3000, AU

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  • 10/F Wharf T&T Centre

    Harbour City, 7 Canton Road

    Tsim Sha Tsui, Kowloon 7, HK

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  • Room730, 7/F, One ICC

    No 999, Middle Huaihai Road

    PR China, Shanghai 200031, CN

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  • 15/F China World Tower 3

    Office #1555 1 Jianguomenwai Avenue

    Chaoyang District, Beijing 100004, CN

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  • Futian New World Centre

    23/F, New World Centre,No. 6009, Yitian Road

    Futian District, Shenzhen 518035, CN

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  • 4 F & 5F GYB Akihabara

    Building 2-25 Kanda Sudacho

    Chiyodaku, Chuo, Tokyo 104-0041, JP

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  • WeWork Koramangala

    Prestige Atlanta 80 Feet Main Road, Koramangala 1A Block Koramangala

    Bengaluru, Karnataka 560034, IN

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  • Seoul Gangnam Haesung

    Building (1905) 4/F, Haesung Building 504 Teheran-ro

    Gangnam-gu, Seoul 06178, KR

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  • First Steps Business Center

    Building 16

    Dubai Internet City, Dubai, AE

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Employees at MongoDB

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Updates

  • View organization page for MongoDB
    MongoDB

    874,977 followers

    With Confluent and MongoDB, you can continuously hydrate your context stores with real-time embeddings, enable RAG, and synchronize data. Check it out 👇

    View organization page for Confluent
    Confluent

    642,081 followers

    Want to build AI agents that collaborate across multi-agent systems, are event-driven, replayable, and grounded in accurate real-time data? Our line-up of 🆕 Streaming Agents features are here to help. Get to know the Real-Time Context Engine, Agent Definition, and everything else new in Streaming Agents—now a part of Confluent Intelligence! 👉 https://cnfl.io/3Jtc78D #Current25 #agenticAI

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  • View organization page for MongoDB
    MongoDB

    874,977 followers

    AI is changing how teams build—and how leaders lead. MongoDB’s Suraj Patel shares with Patrick Steyn what it takes to build responsibly at the speed of AI, why “996 culture” isn’t the only path to innovation, and how the new MongoDB for Startups expansion is helping founders scale smarter. 🎥 ⬇️

  • View organization page for MongoDB
    MongoDB

    874,977 followers

    Lucas Merencia and Giovani Guizzo built SideQuest.js after seeing developers struggle with background jobs in Node.js applications. Lucas created node-cron, which now gets over 5 million downloads per month, but kept seeing people run it inside Express APIs where it would block requests and cause problems in distributed systems. SideQuest.js is a background job processor designed to run jobs in isolation using worker threads, with built-in support for retries, scheduling, and distributed coordination. We talk about the technical decisions behind the architecture, how to migrate from node-cron or other queue systems, and when it makes sense to use SideQuest.js in your applications. - ✅ Try MongoDB 8.0 → https://lnkd.in/dk9kjPyN ✅ Sign-up for a free cluster → https://lnkd.in/gW8cymBx ✅ Subscribe to MongoDB YouTube → https://mdb.link/subscribe - https://sidequestjs.com/

    Building Queues for Node.js with Sidequest.js

    Building Queues for Node.js with Sidequest.js

    www.linkedin.com

  • View organization page for MongoDB
    MongoDB

    874,977 followers

    "Whether it’s teaming up to solve challenging problems or stepping out together for spontaneous tea breaks, spending time together in person brings a lot of value (and fun!). At the same time, I have the freedom to manage my time as I see fit, allowing me to attend family commitments, pursue hobbies that recharge me, and work remotely when needed. Flexible working as been a game-changer for me, but what I enjoy most about MongoDB’s culture is the people — collaborative, supportive, and genuinely invested in each other’s success. Whether its cross-functional teamwork or casual conversations, there’s a strong sense of community and mutual respect. Everyone brings something unique to the table, and that diversity of thought combined with a shared commitment to excellence makes it an inspiring place to work every day." ✨ Sanya Madan, HR Shared Services Lead Learn more about #LifeAtMongoDB and our approach to hybrid working 🔗 https://lnkd.in/gD3J_M_M

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  • View organization page for MongoDB
    MongoDB

    874,977 followers

    Building a RAG app? The embedding model you choose can make or break your retrieval quality. Most developers pick the popular model. Few ask if it’s actually the right one for their data. A great place to start is the Retrieval Embedding Benchmark (RTEB) on Hugging Face RTEB goes beyond traditional benchmarks by evaluating models on both open and private datasets, creating a fair, transparent standard for how embedding models perform on unseen data. When choosing candidate models for evaluation, we recommend focusing on the following columns: 1️⃣ Mean (task): higher = better retrieval quality 2️⃣ Embedding Dimensions: fewer dims = cheaper + faster 3️⃣ Model Size: bigger models = more compute + more $$ (edited) 4️⃣ Max Tokens: higher limits let you embed more text per vector, but too much can hurt retrieval accuracy If you want to check it for yourself, visit the Retrieval Embedding Benchmark (RTEB) Leaderboard on Hugging Face: https://lnkd.in/gQw6K_jZ

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  • MongoDB reposted this

    View organization page for Voyage AI by MongoDB
    Voyage AI by MongoDB

    6,039 followers

    ⚖️ Are LLMs good rerankers? To answer this question, we benchmarked our latest reranker, rerank-2.5, against SOTA LLMs on cost, latency, and accuracy across real-world datasets and multiple first-stage retrieval methods. The verdict: Purpose-built rerankers significantly outperform SOTA LLMs across all metrics. - 11.68%, 12.61%, 13.43% more accurate (NDCG@10) than Claude Sonnet 4.5, GPT-5, and Gemini 2.5 Pro, respectively - 25x cheaper than GPT-5 and Gemini 2.5 Pro, and 60x cheaper than Claude Sonnet 4.5 - 9x, 36x, and 48x faster than Claude Sonnet 4.5, GPT-5, and Gemini 2.5 Pro, respectively Get all the details in our blog: https://lnkd.in/eWtrwF66 Shoutout to Zhenmei Shi , Akshay Goindani, and Hong Liu for their incredible work on this research!

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  • View organization page for MongoDB
    MongoDB

    874,977 followers

    With Matryoshka Representation Learning (MRL), your vector embeddings are like nesting dolls — smaller versions inside larger ones, each retaining the same semantic meaning. Discover how you can reduce storage costs and increase search speed! ➡️ https://lnkd.in/guAEKbis

  • View organization page for MongoDB
    MongoDB

    874,977 followers

    Turn unstructured documents into real-time, searchable intelligence. Our latest walkthrough shows how to build a scalable document processing pipeline with LlamaIndex, Confluent, and MongoDB built for speed, precision, and scale. You’ll learn how to: ✅ Parse complex PDFs with LlamaParse ✅ Stream data in real time with Confluent Cloud ✅ Enrich and store embeddings in MongoDB Atlas for semantic search Explore the full architecture: https://lnkd.in/gVck-urj

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Funding

MongoDB 14 total rounds

Last Round

Post IPO equity
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