Milvus
Pinecone
Qdrant
Weaviate
ElasticSearch
Zilliz Cloud
Vespa.ai
Apache Solr
Split Fee
Unbench
Milvus is a highly flexible, reliable, and blazing-fast cloud-native, open-source vector database. It powers embedding similarity search and AI applications and strives to make vector databases accessible to every organization. Milvus can store, index, and manage a billion+ embedding vectors generated by deep neural networks and other machine learning (ML) models. This level of scale is vital to handling the volumes of unstructured data generated to help organizations to analyze and act on it to provide better service, reduce fraud, avoid downtime, and make decisions faster.
Milvus is a graduated-stage project of the LF AI & Data Foundation.
Split Fee is a platform for UK recruitment agencies to collaborate on permanent placements.
Every agency has candidates they can't place and vacancies they can't fill. Another agency almost certainly has what you need โ but finding them, trusting them, and making the collaboration work has always been the hard part.
Split Fee solves this. Post your candidates and vacancies to the platform. Our matching algorithm finds opportunities across every agency on the network โ by skills, location, salary, and seniority. Candidate and client data stays anonymised until both sides agree to work together. When a placement is made, we handle the fee split and invoicing automatically.
No more posting in social media groups and hoping someone replies. No more sharing candidate details with strangers on trust alone. No more chasing invoices from agencies you barely know.
45% for you. 45% for them. 10% platform fee โ only when a placement is made.
Half of a placement fee is infinitely better than none of it.
Milvus Split FeeNo features have been listed yet.
Milvus is ideal for data scientists, AI researchers, and engineers who require efficient and scalable vector search solutions. It is also recommended for companies and projects dealing with recommendation systems, image and video search, natural language processing, and more.
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Split Fee's answer:
A next-generation serverless platform, built for AWS.
Split Fee's answer:
Split Fee is the first purpose-built platform for split fee recruitment in the UK. Instead of relying on LinkedIn groups, WhatsApp messages, and manual agreements, agencies upload their candidates and vacancies and the platform automatically matches them across agencies.
Candidate identities are revealed gradually; anonymised at first, then progressively disclosed as both sides accept, so agencies can collaborate without the risk of circumvention.
Split Fee's answer:
Most "split fee networks" are just directories or social groups where agencies post and hope someone responds. Split Fee is an actual matching engine. It scores candidate-vacancy pairs, handles the legal agreements (non-circumvention, self-billing), automates invoicing and fee splits, and manages the entire placement lifecycle from match to payment. Everything that normally requires trust, phone calls, and spreadsheets is handled by the platform.
Split Fee's answer:
UK recruitment agencies; from boutique firms with a handful of consultants to mid-sized agencies with specialist sector coverage. Any agency that has either strong candidates without the right vacancies, or client vacancies they can't fill from their own candidate pool. Split Fee turns those dormant assets into placements.
Split Fee's answer:
Abbie, our founder, knew that although split fee arrangements have existed in recruitment for decades, the process has always been manual: find a partner agency, negotiate terms, trust them with your candidate data, chase invoices. Most agencies avoid it because the overhead and risk outweigh the reward. Abbie built Split Fee to remove that friction entirely, with automated matching, progressive identity disclosure, built-in legal agreements, and automated billing, making split placements as straightforward as direct ones.
Based on our record, Milvus seems to be more popular. It has been mentiond 40 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.
More engines. The engine abstraction is clean, adding a new one means implementing four methods (initialize, upsert, search, count). Weaviate, Chroma, and Milvus are very interesting candidates. I should evaluate if they fit the ecosystem and what they offer as peculiarity. Maybe a "plugin system" would be a good implementation to let folks implement their preferred semantic engine. - Source: dev.to / 4 months ago
Weaviate and Milvus: Additional open-source options. - Source: dev.to / 12 months ago
If you like this tutorial, show your support by giving our Milvus GitHub repo a star โญโit means the world to us and inspires us to keep creating! ๐. - Source: dev.to / over 1 year ago
Overview: Milvus is an open-source vector database designed for handling massive-scale vector data. It supports both NNS and ANNS and integrates well with various ML frameworks. - Source: dev.to / almost 2 years ago
If you enjoyed this blog post, consider giving us a star on Github and joining our Discord to share your experiences with the community. - Source: dev.to / about 2 years ago
Pinecone - Search through billions of items for similar matches to any object, in milliseconds. Itโs the next generation of search, an API call away.
Unbench - Beyond recruitment, Unbench became a dynamic matchmaking platform, efficiently connecting companies with top specialists.
Qdrant - Qdrant is a high-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Weaviate - Welcome to Weaviate
ElasticSearch - Elasticsearch is an open source, distributed, RESTful search engine.
Zilliz Cloud - From the creators of Milvus, the vector database trailblazer
