[
  {
    "kind": 1,
    "content": "just another nostr event...",
    "created_at": 1700000000,
    "pubkey": "npub1...",
    "tags": [["e","..."],["p","..."]],
    "id": "...",
    "sig": "..."
  },
  ...
]
        
kind: 0 // permissionless analytics warehouse

Follow your nose
to the signal.

bigNOSTRals is the open-source analytics & data-modeling layer for Nostr — a permissionless DBT-style warehouse that turns raw relay events into clean, queryable tables. Researchers, journalists, and curious engineers can finally smell what the network is really saying.

741M+
Events Indexed
~1.6M
Distinct Authors
~250M
Events / Last 30 Days
~653K
Active Authors / 30 Days

events indexed and counting, rebuilt from the public relay network every day. Follow your nose to the signal.

$ what does bignostrals do

[1] the big nose

Relay Listener

A lightweight client that sniffs public relay events and writes them to a data warehouse. Not a relay — a special kind of client that stays as close to the base Nostr protocol as possible. Raw JSON over WebSockets. No magic, no blind spots.

[2] open analytics engineering

Analytics defined in the open

Every analytical definition — what counts as an active user, how engagement is scored, how a follow is measured — is written as SQL and public. That's the open, transparent way to define analytics about Nostr: fork it, audit it, argue with it, and build on it. Some things get learned by doing.

[3] public datasets

Queryable Tables

Clean, queryable tables on BigQuery. Available upon request today, eventually fully public. Build spam detectors, recommendation engines, academic research, or AI training data — run the queries yourself.

$ built for

📰 journalists

Follow the story

Track how news spreads across the Nostr network. See which relays amplify stories, who the key amplifiers are, and how narratives evolve in real time.

🔬 researchers

Analyse at scale

Query vast quantities of social post data for academic studies. Understand information diffusion, network topology, and community formation patterns.

🧪 data scientists

Feature engineering

A ready-to-use warehouse for feature engineering, backtesting, and model training. Clean tables, documented schemas, reproducible transformations.

🏗️ builders

Easy aggregates

Get high-level metrics (follower counts, post counts, engagement rates) without writing your own ingestion pipeline or running your own relay.

...and much more. If you can query it, you can build on it.

$ what you can sniff out

◣ who's actually here

Daily, weekly, monthly active users

Real active-user counts vs. bot noise, power-user segmentation, cohort and retention curves. Stop guessing how big the network is.

▲ what's catching fire

Trending & viral content

Rank notes by reactions, reposts, replies and zaps into an honest engagement score. Spot what the network is actually paying attention to.

◈ the social graph

Follows & unfollows

Who follows whom, who's gaining and who's losing followers day over day. Watch a narrative spread — or die — one follow at a time.

⚡ where the money moves

Zaps & creator economics

Zap flows, amounts, and who's tipping whom. See the value layer of the protocol — sats follow attention.

◫ the network pulse

Daily network stats

Event volume by kind, active authors, growth over time. A heartbeat monitor for the whole censorship-resistant social layer.

◫ identity & metadata

Profiles & NIP-05

Clean profile metadata, display names, verified identities. The building blocks for discovery, directories, and search.

...and anything else you can think to ask. If you can query it, you can build on it.

Curiosity is a superpower

Have you ever wondered anything in particular about the whole Nostr network? Today is the day you can answer those musings.