Project Euler
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Qdrant
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Qdrant is a leading open-source high-performance Vector Database written in Rust with extended metadata filtering support and advanced features. It deploys as an API service providing a search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications. Powering vector similarity search solutions of any scale due to a flexible architecture and low-level optimization. Qdrant is trusted and high-rated by Machine Learning and Data Science teams of top-tier companies worldwide.
Project Euler
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Qdrant's answer:
Advanced Features, Performance, Scalability, Developer Experience, and Resources Saving.
Qdrant's answer:
Highest performance https://qdrant.tech/benchmarks/, scalability and ease of use.
Qdrant's answer:
Qdrant is written completely in Rust. SDKs available for all popular languages Python, Go, Rust, Java, .NET, etc.
Based on our record, Project Euler should be more popular than Qdrant. It has been mentiond 415 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Let's hope this is going to help me solve some more Project Euler [1] problems! [1] https://projecteuler.net/. - Source: Hacker News / 2 months ago
Https://projecteuler.net/ for "Thinker" brain food. (it still has the issue of not being a pragmatic use of time, but there are plenty interesting enough questions which it at least helps). - Source: Hacker News / 6 months ago
I have a Project Euler (https://projecteuler.net/) account. Though I do not register at all on the leader board I will sometimes work obsessively on a problem just to make one of the level icons light up for me. There is not really competition just a tiny reward. - Source: Hacker News / 7 months ago
I do hobby programing. It is sometimes to create something (supposedly) useful. Lately though it is more discovery and a little math like. I enjoy Project Euler (https://projecteuler.net/. Recently I have been playing with superpermutations (https://projecteuler.net/) and pencil and paper is useful but filling lots of paper with lots of numbers is not that fun. - Source: Hacker News / over 1 year ago
As pointed out in a sibling comment, it appears that quote only shows up if you're logged in, but assuming you have an account and are logged in, it's on the homepage (https://projecteuler.net/), second paragraph under the following heading: > I learned so much solving problem XXX, so is it okay to publish my solution elsewhere? > It appears that you have answered your own question. There is nothing quite like... - Source: Hacker News / over 1 year ago
If you build on the JVM and want to use Qdrant, the official client is io.qdrant:client โ and it's built for Java. Every call returns a ListenableFuture, requests are assembled with protobuf builders, and it drags a gRPC/Netty stack onto your classpath. From Kotlin, that means fighting the language:. - Source: dev.to / about 19 hours ago
The stack runs on Qdrant for vector storage, Ollama for local embeddings, and optional Neo4j for a knowledge graph that I added later. I also set it up to route different operations to the best LLM for each task. It provides eleven tools for your Claude Code instance to manage long-term memory operations, and your memories data never leaves your machine. - Source: dev.to / 5 months ago
Qdrant: Open-source vector database optimized for hybrid search and easy integration with ML workflows. - Source: dev.to / 8 months ago
Yes, Java SDKs are critical. But you don't need to rebuild entire orchestration engines just to write agents in Java. The ecosystem already has platforms solving the hard problems: memory (Zep, Mem0, LangMem), tools (specialized platforms), vectors (Pinecone, Weaviate, Qdrant), observability (LangSmith, Helicone, Langfuse). Integrate, don't rebuild. - Source: dev.to / 9 months ago
James Allsopp adds, "LangChain or LlamaIndex for managing LLM workflows, especially if you're adding vector search or documents." These tools handle multi-step processes, essential for complex apps. - Source: dev.to / 11 months ago
LeetCode - Practice and level up your development skills and prepare for technical interviews.
Weaviate - Welcome to Weaviate
Exercism - Download and solve practice problems in over 30 different languages.
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
Codewars - Achieve code mastery through challenge.
Vespa.ai - Store, search, rank and organize big data