Weaviate Community Edition - Kubernetes Cluster

What do you like best about the product?

The interface is impressively clean and intuitive, making it easy to navigate even as a newcomer to vector databases. The setup and testing process is refreshingly straightforward - you can get up and running quickly without wrestling through complex configuration steps. What really stands out is their commitment to continuous improvement; they're consistently rolling out new products and features that genuinely make the developer experience easier.
Their free office hours, workshops, and events are incredibly valuable for newcomers - having direct access to experts who can answer questions and provide guidance makes the learning curve much more manageable. The integration process feels well-thought-out, and the documentation guides you through implementation without unnecessary complexity.

What do you dislike about the product?

As someone just getting started, it's hard to identify major pain points yet. The learning curve for vector database concepts and who to use them themselves can be steep if you're new to the space, though that's more about the technology category than Weaviate specifically.

What problems is the product solving and how is that benefiting you?

As someone just beginning to explore vector databases, I'm still in the early stages of understanding how Weaviate will fit into my application architecture. From what I've learned so far, Weaviate appears to solve the challenge of efficiently storing and retrieving high-dimensional data for AI applications - particularly for semantic search, recommendation systems, and RAG (Retrieval Augmented Generation) implementations.
While I haven't yet implemented a full production use case, the benefit I'm already seeing is how Weaviate makes vector database concepts more accessible to developers like me who are new to this space. Their clean interface and educational resources (office hours, workshops) are helping me understand not just how to use their product, but how vector databases can enhance applications with more intelligent search and data retrieval capabilities.
I'm exploring use cases around improving search functionality in my applications and potentially implementing AI-powered features, but I'm still in the learning phase of understanding where vector databases provide the most value compared to traditional databases.

What do you like best about the product?

The most helpful about Weaviate is that you can store, vectorize, and search data all within one system — no need to juggle multiple tools and no need to precompute embeddings it has built in vectorization. Also a good community as in it is actively maintained.

What do you dislike about the product?

If you're new, it can feel like you're piecing things together from scattered sources.
Also, it is heavy to run locally. I used it in my windows laptop and my machine used to groan a bit.

What problems is the product solving and how is that benefiting you?

In my solo hackathon project on women’s safety, Weaviate made it super easy to build a fast, intelligent search over incident reports without worrying about vector storage or custom search logic. It saved me hours I would’ve spent wiring up embeddings and let me focus on actually building something useful.

What do you like best about the product?

The tech support is fantastic: ticket ownership, fast turn-around times, professional, personable, and proactively willing share product knowledge with the end user to better help them understand the Weaviate product. Thank you.

What do you dislike about the product?

Nothing. We had one issue with our serverless cloud and Weaviate support assigned four engineers to quickly resolve the issue.

What problems is the product solving and how is that benefiting you?

Vector database tied to our AI workloads.

What do you like best about the product?

Weaviate was so easy to integrate and use. The documentation is easy to follow, the Weaviate AI is super helpful for navigating common problems, and their customer support is next level! Facing a challenge is somehow a pleasant experience - you get a swift response and an expert perspective on your problem.

What do you dislike about the product?

It would've been great to have PHP instructions in the docs, or just simple HTTP requests.

What problems is the product solving and how is that benefiting you?

We're fully replacing our keyword searches to find relevant data for given criteria, with a smart semantic search. Weaviate returns the closest matches and you can further tune them using their RAG functionality by passing the results through Generative AI. It reduces hours of manual work and improves our internal processes immensely.

What do you like best about the product?

I really enjoyed learning about Query agents, transformation agent and personalized agent

What do you dislike about the product?

Nothing, everything was spectacular I enjoyed all the guest speakers

What problems is the product solving and how is that benefiting you?

I am new with Weaviate but hope to use all the knowledge shared to further advance my learning within AI