Add beava to Data Ingestion / ETL → Real-time

[petrpan26]

Adds beava under Data Ingestion / ETL as a new Real-time subcategory (peer to General / Financial Data).

- Real-time
  - [beava](https://github.com/beava-dev/beava) - Real-time feature server for fraud detection, recommender systems, and LLM guardrails; define pipelines in Python and query live per-entity aggregates over HTTP or TCP.

Hidden Gem

beava is one of the very few tools — and possibly the only Python-native OSS one today — that lets you build a real-time feature pipeline with no Kafka and no Flink in the loop. Events go straight into a single Rust binary; the hot path is optimized for sub-millisecond reads (in-memory state, custom framed TCP fast-path), and the next query reflects the push. User surface is Python (@bv.event, @bv.table, bv.count(window="10m")) — same shape as polars or pydantic-core, and pip install beava ships the server binary. Nothing else in the list fills this niche: dlt is batch ETL, faststream is an async broker client, and the Kafka+Flink+feature-store alternatives feel heavy for a fraud or LLM-guardrail signal that should be 15 lines of Python.

Honest about the timing: the public repo is 9 days old after a few months of stealth, so the 3-month consistent-activity bar isn't formally met. Submitting in case the niche feels worth a small exception — totally fair to ask me to come back in August, grateful for the consideration either way.

[petrpan26]

Hi @vinta, completely understandable if this doesn't go through. But I think this is really novel and we are picking up some traction with a few first customers and get a lot of positive response from the developers community !

So hopefully you can help give a consideration.

https://beava.dev/