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Liquid Staking Events
Lido stETH deposits, withdrawals, and claims
Category
Events
Append-only transactions
Granularity
Per-transaction (every staking event)
Format
Apache Parquet
Snappy compression, Hive-partitioned
Nodes
1 (EU-Central)
Frankfurt — low-latency to HyperLiquid & Ethereum
About This Dataset
Every Lido liquid staking event: deposits, withdrawal queue entries, and claims. The macro whale indicator — queued withdrawals predict ETH market supply pressure.
Partitions
protocol:
lidoSchema
| Column | Type | Description |
|---|---|---|
time_chain | timestamp | Block timestamp (UTC) |
time_local | timestamp | Ingestion timestamp (UTC) |
event_type | string | Event: deposit, withdrawal_queued, or claimed |
amount_eth | float64 | Amount in ETH |
staker | string | Staker address |
tx_hash | string | Transaction hash |
Use Cases
- Track net staking inflows and outflows
- Detect large unstaking events that may signal selling pressure
- Analyze correlation between withdrawal queues and ETH price
- Monitor Lido staking APY trends
R2 Path
s3://algotick-data-lake/events/staking_flows/protocol=lido/year=YYYY/month=MM/day=DD/node={node}/data.parquet
Replace
YYYY, MM, DD with the target date.
Data is collected from node=eu-central.
Query with DuckDB
import duckdb df = duckdb.sql(""" SELECT * FROM read_parquet( 's3://algotick-data-lake/events/staking_flows/protocol=lido/year=2026/month=04/day=20/node=eu-central/data.parquet' ) LIMIT 100 """).df() print(f"Rows: {len(df)}, Columns: {list(df.columns)}")
Download via API
import requests resp = requests.get( "https://algotick.dev/v2/history/raw?dataset=staking_flows&protocol=lido&date=2026-04-20", stream=True, ) with open("staking-flows.parquet", "wb") as f: for chunk in resp.iter_content(8192): f.write(chunk) # Then query locally import duckdb df = duckdb.sql("SELECT * FROM 'staking-flows.parquet' LIMIT 100").df() print(df)
Related
Related signals: Whale Activity Volatility
Related datasets: DeFi Lending Yields Bridge Transfer Events
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