Diffbot
import.io
Octoparse
Apify
ParseHub
Data Miner
Kimono
Crawlera
Qdrant
Weaviate
Milvus
Vespa.ai
Pinecone
ElasticSearch
Zilliz
Algolia
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.
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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, Qdrant seems to be a lot more popular than Diffbot. While we know about 64 links to Qdrant, we've tracked only 1 mention of Diffbot. 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.
I work in non-profit/social impact and I'm trying to get a snapshot of themes/issues that concern a subset of organizations (say a total of 500) in our network via news/articles that these orgs may have published or that these orgs may have been referenced in within the last 30-60 days. Using Diffbot (diffbot.com), I can get a list of articles, news, content etc. That relate to these orgs. Understandably, this... Source: about 4 years 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 / 3 days 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
import.io - Import. io helps its users find the internet data they need, organize and store it, and transform it into a format that provides them with the context they need.
Weaviate - Welcome to Weaviate
Octoparse - Octoparse provides easy web scraping for anyone. Our advanced web crawler, allows users to turn web pages into structured spreadsheets within clicks.
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
Apify - Apify is a web scraping and automation platform that can turn any website into an API.
Vespa.ai - Store, search, rank and organize big data