Tags: #scalability
ray-project/ray
Ray is a unified framework for scaling AI and Python applications from a laptop to a cluster, simplifying complex ML workloads with a distributed runtime and specialized libraries.
inclusionAI/AReaL
A scalable asynchronous reinforcement learning infrastructure designed to bridge foundation model training with modern LLM-based agent applications.
milvus-io/milvus
A high-performance, cloud-native vector database designed for scalable Approximate Nearest Neighbor (ANN) search on massive unstructured data.
kyegomez/swarms
An enterprise-grade, production-ready framework for orchestrating complex multi-agent systems, designed for scalable deployments and seamless integration.
polyaxon/polyaxon
A comprehensive MLOps platform for managing, orchestrating, and scaling the machine learning lifecycle with reproducibility and automation.
oceanbase/oceanbase
A high-performance, continuously available, and transparently scalable distributed relational database supporting transactional, analytical, and AI workloads with MySQL compatibility.
predibase/lorax
A multi-LoRA inference server designed to serve thousands of fine-tuned LLMs on a single GPU, significantly reducing serving costs while maintaining high throughput and low latency.
pingcap/tidb
A cloud-native, distributed SQL database offering horizontal scalability, high availability, and HTAP capabilities with MySQL compatibility for unpredictable workloads.
areal-project/AReaL
A scalable asynchronous reinforcement learning infrastructure designed to bridge foundation model training with modern LLM-based agent applications.