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A seamless backend for building powerful AI agents with Langflow + AstraDB
What do you like best about the product?
DataStax made it incredibly easy to build and scale our AI agent with Langflow. AstraDB’s serverless architecture meant we didn’t have to worry about provisioning infrastructure, and the integration with vector search made RAG workflows lightning-fast. We especially loved how well AstraDB plugged into Langflow – it felt like building with building blocks. The documentation is clean, the UI is intuitive, and support was responsive and helpful whenever we had questions. If you’re building anything AI-driven with persistent memory, AstraDB is a no-brainer.
What do you dislike about the product?
While AstraDB is incredibly powerful, the learning curve can be a bit steep for first-time users — especially around schema design and understanding CQL for more complex queries. We also noticed that some SDKs or tooling examples lag behind the latest feature releases, which required digging through docs or GitHub issues. That said, the support team and community are active and helpful when you hit a wall.
What problems is the product solving and how is that benefiting you?
We needed a scalable, low-latency vector database to power our AI agent’s memory and retrieval workflows. DataStax Astra DB gave us exactly that — without the DevOps burden. It helps us manage embeddings efficiently and query them with speed, enabling real-time search and personalized responses inside our Langflow-based LLM app. It’s saved us significant engineering time while allowing us to ship faster and more reliably.
Datastax and Langflow - Interconnected Systems to Build and Prototype RAG Applications Easily
What do you like best about the product?
As a company building and stress-testing RAG pipelines daily, the combination of DataStax Astra DB and Langflow has been a game-changer. DataStax delivers scalable, high-speed vector search with excellent integration via the Astra DB and LangChain ecosystem—perfect for low-latency, high-volume workloads. Langflow, on the other hand, makes LLM orchestration visual and intuitive. It accelerates prototyping while still being customizable enough for production-grade workflows. Together, they reduce dev time significantly and let me focus more on refining prompts and grounding logic, rather than infrastructure.
Pros:
Astra DB’s fast vector search and native LangChain support
Langflow’s drag-and-drop interface for rapid experimentation
Easy integration with OpenAI, Cohere, and other providers
Scales well without overcomplicating the stack
Pros:
Astra DB’s fast vector search and native LangChain support
Langflow’s drag-and-drop interface for rapid experimentation
Easy integration with OpenAI, Cohere, and other providers
Scales well without overcomplicating the stack
What do you dislike about the product?
Langflow is Currently in Preview which might limit deployment to Production Environments
What problems is the product solving and how is that benefiting you?
Helping us build and iterate RAG Workflows at scale with simple UI and Testing
Personal review
What do you like best about the product?
DataStax offers high performance, scalability, and enterprise-grade features built on Apache Cassandra, making it ideal for handling large-scale, real-time data.
What do you dislike about the product?
Setting up and managing it can be complex, especially for beginners, and pricing may be high for smaller teams.
What problems is the product solving and how is that benefiting you?
DataStax makes it easy to handle big data and ensures high availability with minimal downtime. It helps us scale smoothly and manage data across multiple locations.
Overview
What do you like best about the product?
Scalability of architecture
Less downtime
Less downtime
What do you dislike about the product?
Nothing so far,
Still observing the system
Still observing the system
What problems is the product solving and how is that benefiting you?
Downtime reduction
DataStax brings no-code AI Agents to life
What do you like best about the product?
Very easy to implement. Vast integrations with LLMs and databases. Easy and intuitive to use
What do you dislike about the product?
The way Agents, tools, databases etc... connect can vary from one day to the other, significantly leading to the AI Agents' flows becoming unusable
What problems is the product solving and how is that benefiting you?
The databases are really easy to implement
Langflow by DataStax is hands down the best for multi-agent systems.
What do you like best about the product?
As a dev who wants to get things done while staying flexible, this is a dream come true. You get all the drag-and-drop components for speed and simplicity - but you’re not locked in. You can create your own components and tweak almost anything to fit your needs.
This means you can build complex components while still working with intuitive, easy-to-grasp flows. Custom code can quickly become a tangled mess, and no-code builders can feel too restrictive. Langflow strikes the perfect balance.
Plus, it’s open-source, with a thriving community that’s making it better every day!
You’ve just got to try it. I keep going to langflow.new whenever I want to test something real quick since there’s no login, and you can jump right in. 😄
This means you can build complex components while still working with intuitive, easy-to-grasp flows. Custom code can quickly become a tangled mess, and no-code builders can feel too restrictive. Langflow strikes the perfect balance.
Plus, it’s open-source, with a thriving community that’s making it better every day!
You’ve just got to try it. I keep going to langflow.new whenever I want to test something real quick since there’s no login, and you can jump right in. 😄
What do you dislike about the product?
I only see two downsides.
First, it has fewer integrations compared to other no-code tools like Make.com or n8n. That said, the crucial ones like Google Drive ,Gmail, etc. are already there. Plus, it’s more optimized for agentic systems, where it actually has the most integrations of any platform (vector DBs, model providers, etc.), so it makes sense.
Second, startup time and initial runs can be a bit slow. Given how much functionality it packs, that’s understandable. But I’ve already seen huge improvements in this area, so I’m pretty confident it’ll keep getting better over time.
First, it has fewer integrations compared to other no-code tools like Make.com or n8n. That said, the crucial ones like Google Drive ,Gmail, etc. are already there. Plus, it’s more optimized for agentic systems, where it actually has the most integrations of any platform (vector DBs, model providers, etc.), so it makes sense.
Second, startup time and initial runs can be a bit slow. Given how much functionality it packs, that’s understandable. But I’ve already seen huge improvements in this area, so I’m pretty confident it’ll keep getting better over time.
What problems is the product solving and how is that benefiting you?
Super quick and easy vector DB setup for Langflow!
A great way to learn to build AI applications and agents
What do you like best about the product?
It’s easy to start learning and building right away
What do you dislike about the product?
I can’t think of anything right away. Developers may have a different opinion.
What problems is the product solving and how is that benefiting you?
I used DataStax to build a demo that I can show to customers
DataStax has enabled us to build out game-changing features in our product
What do you like best about the product?
DataStax offers next-level customer support with a great product. The team is always available and eager to help. Astra DB has allowed us to build out some pretty unique features that our customers are loving. I'd recommend their tech to anyone building an AI-first company.
What do you dislike about the product?
We have not had any issues. The DataStax team and product have been great.
What problems is the product solving and how is that benefiting you?
We're using DataStax's products to enhance our ability to offer a unique and customizable experience with our product. Without going into our IP too much, DataStax has enabled some key features that have helped us to stay meaningfully differentiated.
Best Vector DB in the market
What do you like best about the product?
Advanced vector search capabilities, real-time processing, and fully managed database services.
What do you dislike about the product?
Overall the experience was good while leveraging Datastax Astra DB.
What problems is the product solving and how is that benefiting you?
Managing vast volumes of unstructured data across domains required a database solution capable of handling high-throughput, low-latency queries while ensuring data relevance and accuracy.
Seamless communication between your app & cassandra
What do you like best about the product?
Simplified database operations with builtin support for query execution.
DataStax's QueryBuilder API can handle diverse types of queries
DataStax's QueryBuilder API can handle diverse types of queries
What do you dislike about the product?
Learning curve can be steep because of their long list of Query APIs.
What problems is the product solving and how is that benefiting you?
Datastax help overcome the complexity of handling distributed database systems like cassandra.
The drivers can efficiently interact with cassandra without compromising on latency and HA
The drivers can efficiently interact with cassandra without compromising on latency and HA
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