Travis CI
Jenkins
CircleCI
Codeship
Buddy
TeamCity
Azure DevOps
Bitrise
Weaviate
Qdrant
Milvus
pgvecto.rs
txtai
Zilliz
Vespa.ai
EVA DB
Travis CI WeaviateBased on our record, Weaviate should be more popular than Travis CI. 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.
We used Travis CI for our continuous integration (CI) pipeline. Travis is a highly popular CI on Github and its build matrix feature is useful for repositories which contain multiple projects like Grab's. We configured Travis to do the following:. - Source: dev.to / over 1 year ago
CI/CD for autobuild + autotests (Codemagic or Travis CI). Source: over 1 year ago
Step 2: Log on to Travis CI and sign up with your GitHub account used above. - Source: dev.to / almost 2 years ago
Some other hosted CI products, such as CircleCI and Travis Cl, are completely hosted in the cloud. It is becoming more popular for small organizations to use hosted CI products, as they allow engineering teams to begin continuous integration as soon as possible. Source: almost 3 years ago
1. Let's create the account. Access the site https://travis-ci.com/ and click on the button Sign up. - Source: dev.to / almost 3 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
Jenkins - Jenkins is an open-source continuous integration server with 300+ plugins to support all kinds of software development
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/
CircleCI - CircleCI gives web developers powerful Continuous Integration and Deployment with easy setup and maintenance.
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
Codeship - Codeship is a fast and secure hosted Continuous Delivery platform that scales with your needs.
pgvecto.rs - Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. - tensorchord/pgvecto.rs
