🔄

DEX Swaps

On-chain DEX swap events from Uniswap, Aerodrome, Jupiter, and more

About This Dataset

Per-transaction DEX swap events across Base, Arbitrum, and Solana. Each swap includes pool address, token pair, amounts, USD value, and transaction hash.

Partitions

chain: base, arbitrum, solana

Schema

Column	Type	Description
`time_chain`	`timestamp`	Block timestamp (UTC)
`time_local`	`timestamp`	Ingestion timestamp (UTC)
`pool`	`string`	Pool/pair contract address
`token_in`	`string`	Input token symbol
`token_out`	`string`	Output token symbol
`amount_in`	`float64`	Input amount (native units)
`amount_out`	`float64`	Output amount (native units)
`amount_usd`	`float64`	Swap value in USD
`tx_hash`	`string`	Transaction hash
`dex`	`string`	DEX protocol name

Use Cases

Analyze DEX volume distribution by protocol and chain
Detect large swaps (whale activity) in real-time
Track token-level buy/sell pressure on-chain
Build Solana or L2 DEX trading strategies

R2 Path

s3://algotick-data-lake/events/swaps/chain={chain}/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/swaps/chain=base/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=swaps&chain=base&date=2026-04-20",
    stream=True,
)

with open("swaps.parquet", "wb") as f:
    for chunk in resp.iter_content(8192):
        f.write(chunk)

# Then query locally
import duckdb
df = duckdb.sql("SELECT * FROM 'swaps.parquet' LIMIT 100").df()
print(df)

Get API Key →

Related signals: Whale Activity Volatility

Don't just stare at the dashboard. Automate it.

Every metric on this page is available via our sub-millisecond API.
Build trading bots, backtest strategies, and power AI agents with institutional-grade data.

Explore API →

Continue the Research

⚡ API Reference 🍳 Cookbook 📊 Backtests 📖 Playbooks