Jenkins
CircleCI
Codeship
Travis CI
Ansible
Bamboo
Bitrise
Buddy
Weaviate
Qdrant
Milvus
pgvecto.rs
txtai
Zilliz
Vespa.ai
EVA DB
Jenkins WeaviateBased on our record, Weaviate should be more popular than Jenkins. It has been mentiond 28 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.
It will give you a possibility to find and solve problems faster, release more stable and higher quality products. Here we will use CircleCI, but you can use whatever you need (Jenkins, Travis CI, GitLab CI). - Source: dev.to / 22 days ago
CloudBees Jenkins Platform is a commercial offering from CloudBees, it is not the Jenkins project itself (which is open source). Jenkins is alive and well. See https://jenkins.io. Source: 12 months ago
Ok. I'm talking about this: https://jenkins.io/. Source: over 1 year ago
Currently supported : Datadog, Jenkins, DNS, HTTP. Source: over 1 year ago
Saw this new blog post on jenkins.io which is really cool. Basically it is a free tool that you can use to help make sure your Jenkins system is managed well. Source: over 2 years ago
Weaviate: An open-source, cloud-native vector database built for scalable and fast vector searches. It's particularly effective for semantic search applications, combining full-text search with vector search for AI-powered insights. - Source: dev.to / 3 months ago
Weaviate is an open-source vector search engine with out-of-the-box support for vectorization, classification, and semantic search. It is designed to make vector search accessible and scalable, supporting use cases such as semantic text search, automatic classification, and more. - Source: dev.to / 4 months ago
Congrats to them! What have your experiences with vector databases been? I've been using https://weaviate.io/ which works great, but just for little tech demos, so I'm not really sure how to compare one versus another or even what to look for really. - Source: Hacker News / 4 months ago
A RAG implementation's quality and performance highly depend on the similarity-based search of embeddings. The challenge arises from the fact that embeddings are usually high-dimensional vectors, and the knowledge base may have many documents. It's not surprising that the popularity of LLM catalyzed the development of specialized vector databases like Pinecone and Weaviate. However, SQL databases are also evolving... - Source: dev.to / 5 months ago
To find semantically similar texts we need to calculate the distance between vectors. While we have just a few short texts we can brute-force it: calculate the distance between our query and each text embedding one by one and see which one is the closest. When we deal with thousands or even millions of entries in our database, however, we need a more efficient way of comparing vectors. Just like for any other way... - Source: dev.to / 7 months ago
CircleCI - CircleCI gives web developers powerful Continuous Integration and Deployment with easy setup and maintenance.
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/
Codeship - Codeship is a fast and secure hosted Continuous Delivery platform that scales with your needs.
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
Travis CI - Focus on writing code. Let Travis CI take care of running your tests and deploying your apps.
pgvecto.rs - Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. - tensorchord/pgvecto.rs