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vectordb is a Pythonic vector database offers a comprehensive suite of CRUD (Create, Read, Update, Delete) operations and robust scalability options, including sharding and replication. It's readily deployable in a variety of environments, from local to on-premise and cloud. vectordb delivers exactly what you need - no more, no less. It's a testament to effective Pythonic design without over-engineering, making it a lean yet powerful solution for all your needs. vectordb capitalizes on the powerful retrieval prowess of DocArray and the scalability, reliability, and serving capabilities of Jina. Here's the magic: DocArray serves as the engine driving vector search logic, while Jina guarantees efficient and scalable index serving. ...

...It has great features such as file-based backup, and metrics-based ordering of Agents. Also, Vald is highly configurable using YAML files. It works without Kubernetes, single binary (less than 30MB), easy to run (can be configured by command-line options), and consists of Agent and Server. alvd has almost the same features as Vald's gateway-lb + discoverer and agent-ngt. alvd depends on Vald codebase, the files came from Vald (such as internal, pkg/vald. They are downloaded when running make command.) are excluded from my license and ownership.