MongoDB Atlas Vector is highly praised for its seamless integration capabilities, especially for developers working with PHP and AI applications. Users commend its robust vector search functionality and real-time data handling, as highlighted by the positive ratings averaging around 4.8/5 on platforms like G2. However, there are few mentions of specific complaints, suggesting a general satisfaction with the tool. Pricing sentiment appears positive, with users not expressing concerns over costs, and overall, MongoDB Atlas Vector enjoys a strong reputation for aiding skill development and promoting community engagement through initiatives like skill badges and user groups.
Mentions (30d)
37
15 this week
Avg Rating
4.5
20 reviews
Platforms
3
Sentiment
10%
10 positive
MongoDB Atlas Vector is highly praised for its seamless integration capabilities, especially for developers working with PHP and AI applications. Users commend its robust vector search functionality and real-time data handling, as highlighted by the positive ratings averaging around 4.8/5 on platforms like G2. However, there are few mentions of specific complaints, suggesting a general satisfaction with the tool. Pricing sentiment appears positive, with users not expressing concerns over costs, and overall, MongoDB Atlas Vector enjoys a strong reputation for aiding skill development and promoting community engagement through initiatives like skill badges and user groups.
Features
Use Cases
Industry
information technology & services
Employees
5,600
502,300
Twitter followers
Better Database Authentication with Better-Auth https://t.co/f0ufzb3Hm9
Better Database Authentication with Better-Auth https://t.co/f0ufzb3Hm9
View originalg2
What do you like best about MongoDB Atlas?I use MongoDB Atlas for hosting our MongoDB, and I appreciate its reliability; I've never had any problems with its uptime. I really like the tools it offers for scaling and performance monitoring, as they are easy to use with a nice user interface. It's great that new MongoDB versions are deployed as soon as they are released, allowing me to use new features without any delay. The initial setup was easy without any problems, which I really value. Review collected by and hosted on G2.com.What do you dislike about MongoDB Atlas?I think their alerting system may be a bit improved, for example so I can setup more granular alerts. For example, I can't set up composite rules (for example error rate of specific endpoint + CPU threshold, etc). Basically, it's limited in customization. Review collected by and hosted on G2.com.
What do you like best about MongoDB Atlas?easy UI, very intuitive, good documentation Review collected by and hosted on G2.com.What do you dislike about MongoDB Atlas?there is nothing I dislike - customer support might respond faster Review collected by and hosted on G2.com.
What do you like best about MongoDB Atlas?Automated scaling, backups, monitoring and performance alerts make it incredibly easy to maintain clusters without dedicating a team to infrastructure. Added to that, the UI is intuitive, queries run fast and features like Atlas Search, Charts and built-in security controls help ship features quickly. Review collected by and hosted on G2.com.What do you dislike about MongoDB Atlas?Some configuration options feel hidden behind tiers. Also, greater transparency around cost optimization or in-platform recommendations would make the experience even smoother. Review collected by and hosted on G2.com.
What do you like best about MongoDB Atlas?I appreciate MongoDB Atlas for making database management more user-friendly with its intuitive UI, which makes it more comfortable to work with compared to using only the terminal. The feature for managing MongoDB aggregations is particularly beneficial, allowing me to build queries from smaller parts efficiently and intuitively, making the process significantly easier than doing it manually. I highly value how MongoDB Atlas helps me work seamlessly with databases, especially when I am developing and need to check the state of my data. Its performance is fast, which I like, and it integrates well when I am working on the backend with Visual Studio Code. Overall, it's easy to set up if environment variables are configured correctly, making the whole process straightforward. Review collected by and hosted on G2.com.What do you dislike about MongoDB Atlas?I think it works great , I don't see anything to improve particularly Review collected by and hosted on G2.com.
What do you like best about MongoDB Atlas?Flexibility, Ease of use and efficiency as well database connection and interaction while development phase. Review collected by and hosted on G2.com.What do you dislike about MongoDB Atlas?For the NoSQL databases, it's fine; I didn't feel that anything was wrong. Review collected by and hosted on G2.com.
What do you like best about MongoDB Atlas?simplicity, ease of use, scaling, sharding, data management Review collected by and hosted on G2.com.What do you dislike about MongoDB Atlas?Sometimes the database clusters take time while loading the data Review collected by and hosted on G2.com.
What do you like best about MongoDB Atlas?It good as it store different types of data structures, different types of documents as it as good scalability and has good performance. Review collected by and hosted on G2.com.What do you dislike about MongoDB Atlas?It doesn't support multi document ACID and contains high memory usage which has data inconsistencies sometimes. Review collected by and hosted on G2.com.
What do you like best about MongoDB Atlas?I use MongoDB Atlas for a document database and appreciate its faster response and easy search with indexing. I really like sharding in MongoDB Atlas because it splits the data equally to all the nodes, which allows it to handle multiple reads and write operations. Setting up MongoDB Atlas is straightforward and easy. Review collected by and hosted on G2.com.What do you dislike about MongoDB Atlas?I am not a fan of the default ID that MongoDB Atlas creates for every entry. Review collected by and hosted on G2.com.
What do you like best about MongoDB Atlas?I have nothing good to say about MongoDB Atlas. Review collected by and hosted on G2.com.What do you dislike about MongoDB Atlas?My story with Mongo began when I started a new software position, and they had a legacy version of their software product using Atlas. Compared to our other infrastructure bills, Mongo was significantly higher for the amount of compute and storage we used ($3K per month). This is a managed service, so you would expect to pay a premium. Ok, sure, but then I expect great functionality, performance, and support. The main problem began with Mongo when we needed to delete some data because they tie the CPU and memory tiers to storage size, so we were overpaying. Our application would run fine off an M10 dedicated cluster (the smallest tier), but it had automatically scaled to an M50 because of storage. This is already a bit disappointing because they are forcing customers to pay for more compute and memory than they need. So we started deleting some data, but then we ran into problems. The data deletion process was really slow and also slowed our entire cluster down, causing lag and performance issues for our end users. But hang on, this makes no sense because we are paying for more CPU and RAM than we need, so why would we have this issue? It took us three months to delete 500GB of data. In the meantime, our bill remained the same because you can't claim the space back without compacting the database. Ok, fine. So we ran compact(), but we only freed ~100GB on the secondary clusters. Support gave us a script to run that can see how much storage can be freed. In the end, we had to activate an expensive additional support plan costing us $500 USD per month to get support to run a re-sync command. This should have taken their support people 10 minutes, but instead, they mucked us around going back and forth on the ticket, taking three weeks to resolve. A year later, we needed to delete some more data. We spent another five months deleting 800GB of data. Then we ran compact() and freed 300GB. Where is our other 500GB? We contacted some humans at Mongo, who really couldn't do much other than suggest we get funding to cover the $500 support for one month. Yes, we got the $500 credit, but when I went to reactivate support, it was going to charge us for three months for one month because Mongo retroactively bills you for three months when you reactivate. Wow, we started in a bad place, now I'm beyond frustrated; this is daylight robbery. To this day, I am still fighting to reclaim some storage, but at this point, I'm going to recommend to our CEO that our dev team put some effort into moving away completely from Mongo. I also need to mention that Mongo recommended we use their online archive features, but when we crunched the numbers, it was still quite expensive, and we would have to do significant work to make our application work between the regular clusters and online archive. So it was significantly more logical to just put the data in AWS S3, then delete it in Mongo. If I can summarize my experience with Mongo, and I acknowledge mine is probably quite different to most, here it is: Overpriced for the performance you get Sneaky billing model where they tie CPU and memory to storage Terrible and expensive support Sneaky extra charges on reactivating support Bad support escalation solutions - they couldn't just turn on free 'support' Poor database performance Slow delete operations Ecosystem lock-in Forced upgrades - no LTS releases Let me sum it up this way: if your compact() command does not free up the space that is available on your cluster, then provide the customer with free support to do so. I hate dealing with Mongo. Nothing is simple, everything is expensive, and the performance sucks. If you are considering using Mongo, find something else. Even if you have to take a bit more time to learn AWS Dynamo, S3, or Aurora, you should do it; you will save time and money in the long run. Mongo, you deserve this negative review. I have given you plenty of opportunities to resolve things and have escalated issues, but you just don't care. We wanted to move away from Mongo before; now I can't get rid of it fast enough. Review collected by and hosted on G2.com.
What do you like best about MongoDB Atlas?Portability, easy to fire up, and requires less resource Review collected by and hosted on G2.com.What do you dislike about MongoDB Atlas?So far nothing I have found that concerns me about mongo Review collected by and hosted on G2.com.
A lot shipped at MongoDB.local London today. New capabilities, new integrations, new ways to build production AI. If you weren't in the room, the livestream is on demand with everything you need t
A lot shipped at MongoDB.local London today. New capabilities, new integrations, new ways to build production AI. If you weren't in the room, the livestream is on demand with everything you need to catch up. → https://t.co/b55DjcxNH3 https://t.co/OzV1YiStw8
View originalAI-native applications don’t stay in conference rooms. Neither did we 🚕 📸 Keep an eye out across London and tag us for a chance to be featured. #MongoDBlocal https://t.co/8gBLEDFRMt
AI-native applications don’t stay in conference rooms. Neither did we 🚕 📸 Keep an eye out across London and tag us for a chance to be featured. #MongoDBlocal https://t.co/8gBLEDFRMt
View original🇬🇧 🎤A full day of conversations at #MongoDBlocal London. On stage: @cj_mongodb, @UlkuRowe of @lbgplc, @LucianaLix of @Sequoia, and Alexander Holt of @Elevenlabs. https://t.co/ArfOp7GqIG
🇬🇧 🎤A full day of conversations at #MongoDBlocal London. On stage: @cj_mongodb, @UlkuRowe of @lbgplc, @LucianaLix of @Sequoia, and Alexander Holt of @Elevenlabs. https://t.co/ArfOp7GqIG
View original“LLMs are here to stay. The data layer is here to stay. The agent layer is here to stay. Everything else is in question.” @cj_mongodb sat down with @harrystebbings to talk about what stays constant a
“LLMs are here to stay. The data layer is here to stay. The agent layer is here to stay. Everything else is in question.” @cj_mongodb sat down with @harrystebbings to talk about what stays constant as AI reshapes the stack, and why the data layer is at the center of it. https://t.co/GLcrgQ6b7V
View originalWe just dropped 3 🆕 AI Skill Badges 💫 Our new skill badges focus on the abilities that separate prototype AI from production AI. Earn all three, add them to your profile, and show the world you bu
We just dropped 3 🆕 AI Skill Badges 💫 Our new skill badges focus on the abilities that separate prototype AI from production AI. Earn all three, add them to your profile, and show the world you build AI that works ➡️ https://t.co/fHwC6l28ZB https://t.co/XY2FsX9uCg
View original@VoyageAI @awscloud We're launching three new MongoDB AI Skill Badges. 🎓 Prove your expertise building production AI on MongoDB: → Voyage AI with MongoDB → Vector Search Performance → Memory for AI
@VoyageAI @awscloud We're launching three new MongoDB AI Skill Badges. 🎓 Prove your expertise building production AI on MongoDB: → Voyage AI with MongoDB → Vector Search Performance → Memory for AI Applications Earn yours today ⬇️ https://t.co/PX6ml8XtDK
View original@VoyageAI @awscloud Stop fighting infrastructure and start building AI 💪 Learn more about everything we announced at MongoDB.local London ⬇️ https://t.co/mfwHIyP62O
@VoyageAI @awscloud Stop fighting infrastructure and start building AI 💪 Learn more about everything we announced at MongoDB.local London ⬇️ https://t.co/mfwHIyP62O
View original@VoyageAI Cross-Region Connectivity Support for @awscloud PrivateLink is now generally available. Multi-region Atlas deployments can now communicate without requiring VPC Peering, using PrivateLink n
@VoyageAI Cross-Region Connectivity Support for @awscloud PrivateLink is now generally available. Multi-region Atlas deployments can now communicate without requiring VPC Peering, using PrivateLink natively across regions ⬇️ https://t.co/1gmvfmDiUk
View original@VoyageAI The Feast Feature Store Integration is now generally available 🙌 MongoDB now serves as both an offline and online feature store for your AI workloads. One database to secure, monitor, and
@VoyageAI The Feast Feature Store Integration is now generally available 🙌 MongoDB now serves as both an offline and online feature store for your AI workloads. One database to secure, monitor, and optimize—with the same enterprise controls your applications already rely on in Atlas ⬇️
View original@VoyageAI LangGraph.js Long-Term Memory Store is now generally available 🎉 This integration brings long-term memory across sessions, across users, and across time, with Atlas as the unified backend
@VoyageAI LangGraph.js Long-Term Memory Store is now generally available 🎉 This integration brings long-term memory across sessions, across users, and across time, with Atlas as the unified backend for checkpointing and semantic recall, powered by Voyage AI embeddings ⬇️
View originalMongoDB 8.3 is now generally available. Up to 35% more writes. 45% more reads. 15% more ACID transactions. All without changing a line of application code ⬇️ https://t.co/7JjIuvllUH
MongoDB 8.3 is now generally available. Up to 35% more writes. 45% more reads. 15% more ACID transactions. All without changing a line of application code ⬇️ https://t.co/7JjIuvllUH
View originalAutomated Voyage Embeddings in MongoDB Vector Search is now in public preview ✨ Pick a @VoyageAI model, create an index, and MongoDB keeps your embeddings synced automatically as data changes. No pi
Automated Voyage Embeddings in MongoDB Vector Search is now in public preview ✨ Pick a @VoyageAI model, create an index, and MongoDB keeps your embeddings synced automatically as data changes. No pipeline management. No stale context ⬇️ https://t.co/RItoCmzH8N
View originalWe shipped new capabilities at MongoDB.local London to deliver a unified AI data platform that gives enterprises everything they need to run agents in production 🔥 Here’s what’s new 👇 https://t.co/
We shipped new capabilities at MongoDB.local London to deliver a unified AI data platform that gives enterprises everything they need to run agents in production 🔥 Here’s what’s new 👇 https://t.co/iRN1A7bzkw
View original🎙️🔴 LIVE from London: today we're bringing together the developers, architects, and enterprise teams shipping AI-native applications on MongoDB, and streaming it all for those who can't be here. If
🎙️🔴 LIVE from London: today we're bringing together the developers, architects, and enterprise teams shipping AI-native applications on MongoDB, and streaming it all for those who can't be here. If you're building with AI, this is where the conversation is happening. 🇬🇧 WATCH https://t.co/bwndeneSEk
View originalLIVE From MongoDB .local London 2026! https://t.co/NjGYdFzNnL
LIVE From MongoDB .local London 2026! https://t.co/NjGYdFzNnL
View originalMongoDB Atlas Vector uses a subscription + tiered pricing model. Visit their website for current pricing details.
MongoDB Atlas Vector has an average rating of 4.5 out of 5 stars based on 20 reviews from G2, Capterra, and TrustRadius.
Key features include: General Information, Documentation, Community Forums, University, Manage Consent Preferences, Strictly Necessary Cookies, Opt Out of Third Party Cookies, Cookie List.
MongoDB Atlas Vector is commonly used for: Medical consultation analysis, Recommendation systems for e-commerce, Natural language processing applications, Image and video content retrieval, Fraud detection in financial services, Customer sentiment analysis.
MongoDB Atlas Vector integrates with: VoyageAI for embeddings, Apache Kafka for data streaming, AWS for cloud infrastructure, Google Cloud Platform for scalability, Microsoft Azure for hybrid cloud solutions, Elasticsearch for advanced search capabilities, Grafana for monitoring and analytics, Kubernetes for container orchestration, Jupyter Notebooks for data science workflows, TensorFlow for machine learning model deployment.
Based on user reviews and social mentions, the most common pain points are: down.
Based on 102 social mentions analyzed, 10% of sentiment is positive, 90% neutral, and 0% negative.