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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.
OpenStreetMap
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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, OpenStreetMap should be more popular than Qdrant. It has been mentiond 130 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.
Finally, to ensure a visually harmonious experience, the design of the integrated modern map, which utilizes OpenStreetMap (OSM) data, has been carefully styled to match the aesthetic and color palette of the original Rekichizu historical map. - Source: dev.to / 8 months ago
You can go to https://openstreetmap.org/ , zoom in and enable the map data layer. From there history is accessible. - Source: Hacker News / over 2 years ago
Hi! I am working on a project mapping bike racks around my city on OpenStreetMap. One of the attributes that I tag is the rack's capacity, but I haven't come to a conclusion about the capacity of these wave-shaped racks:. Source: over 2 years ago
I need the bounding boxes of all adminstrative units in a specific region from the largest (e.g. The state) to the smallest (whatever this is called) including the full name of the district. What I mean by that is what is displayed on openstreetmap.org when I search for e.g. Brooklyn: it will be displayed in the search results as "Brooklyn, Kings County, New York, United States of America" โ the names joined from... Source: over 2 years ago
It's OpenStreetMap (ODbL) and Natural Earth (public domain) currently * http://openstreetmap.org * http://naturalearthdata.com. - Source: Hacker News / over 2 years 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
๐ฆ Qdrant for fast vector search and retrieval. - Source: dev.to / 12 months ago
Google Maps - Find local businesses, view maps and get driving directions in Google Maps.
Weaviate - Welcome to Weaviate
HERE WeGo - HERE WeGo - Maps - Routes - Directions - All ways from A to B in one
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
Apple Maps - Maps features an all-new design with smart features to make finding and getting to your destination easier than ever.
Vespa.ai - Store, search, rank and organize big data