ThalamusDB: Query text, tables, images, and audio
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Show HN: Minikv – Distributed key-value and object store in Rust (Raft, S3 API)
Show HN: Minikv – Distributed key-value and object store in Rust (Raft, S3 API) Hi HN,<p>I’m releasing minikv, a distributed key-value and object store in Rust.<p>What is minikv? minikv is an open-source, distributed storage engine built for learning, experimentation, and self-hosted setups. It combines a strongly-consistent key-value database (Raft), S3-compatible object storage, and basic multi-tenancy. I started minikv as a learning project about distributed systems, and it grew into something production-ready and fun to extend.<p>Features/highlights:<p>- Raft consensus with automatic failover and sharding - S3-compatible HTTP API (plus REST/gRPC APIs) - Pluggable storage backends: in-memory, RocksDB, Sled - Multi-tenant: per-tenant namespaces, role-based access, quotas, and audit - Metrics (Prometheus), TLS, JWT-based API keys - Easy to deploy (single binary, works with Docker/Kubernetes)<p>Quick demo (single node):<p>git clone <a href="https://github.com/whispem/minikv.git" rel="nofollow">https://github.com/whispem/minikv.git</a> cd minikv cargo run --release -- --config config.example.toml curl localhost:8080/health/ready # S3 upload + read curl -X PUT localhost:8080/s3/mybucket/hello -d "hi HN" curl localhost:8080/s3/mybucket/hello<p>Docs, cluster setup, and architecture details are in the repo. I’d love to hear feedback, questions, ideas, or your stories running distributed infra in Rust!<p>Repo: <a href="https://github.com/whispem/minikv" rel="nofollow">https://github.com/whispem/minikv</a> Crate: <a href="https://crates.io/crates/minikv" rel="nofollow">https://crates.io/crates/minikv</a>
CLI's completion should know what options you've typed
CLI's completion should know what options you've typed
Show HN: Python SDK – forecasting with foundation time-series and tabular models
Show HN: Python SDK – forecasting with foundation time-series and tabular models We’ve built a Python SDK for running inference on foundation models designed for time-series and tabular data. They are new SOTA models for time-series and tabular tasks and work out of the box. They do not require model training or feature engineering. The link to the GitHub repository is: <a href="https://github.com/S-FM/faim-python-client" rel="nofollow">https://github.com/S-FM/faim-python-client</a>
Show HN: Deterministic PCIe Diagnostics for GPUs on Linux
Show HN: Deterministic PCIe Diagnostics for GPUs on Linux I built a small Linux tool to deterministically verify GPU PCIe link health and bandwidth.<p>It reports: - Negotiated PCIe generation and width - Peak Host→Device and Device→Host memcpy bandwidth - Sustained PCIe TX/RX utilization via NVML - A rule-based verdict derived from observable hardware data only<p>This exists because PCIe issues (Gen downgrades, reduced lane width, risers, bifurcation) are often invisible at the application layer and can’t be fixed by kernel tuning or async overlap.<p>Linux-only: it relies on sysfs and PCIe AER exposure that Windows does not provide.
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