Quick start

Koinju delivers institutional-grade crypto market data — tick trades (418 billion+ since 2013), OHLCV candles, funding rates, and recomputed option Greeks — across 13 exchanges under one normalized schema.

Two ways in: a REST API for simple pulls, and direct SQL (ClickHouse) for bulk analytics and server-side compute. See Pricing for tiers.

Zero to a plotted BTC chart in three steps. Full connector reference (Rust, Go, CLI, BI tools, REST) is in How to connect.

Using an AI coding agent? Install the Koinju agent skill so Claude Code / Cursor / Copilot already know the schema, auth, and query patterns and can help you get started with Koinju API faster.

npx skills add https://gitlab.com/koinju-public/agent-skill

1. Get credentials

You need a database URL (host), username, and password. Sign up at koinju.io/pricing to get them, or email [e-mail].

2. First SQL query (Python)

pip install clickhouse-connect pandas matplotlib

import clickhouse_connect

conn = clickhouse_connect.get_client(
    host="<provided_database_url>",
    port=8443,
    secure=True,
    username="<username>",
    password="<password>",
    database="api",
)

df = conn.query_df(
    """
    SELECT start, exchange, market, toFloat64(close) AS close
    FROM api.ohlcv(candle_duration_in_minutes = 1440)
    WHERE market IN ('BTC-USD', 'BTC-USDT')
      AND start >= now() - INTERVAL 90 DAY
    ORDER BY start
    """
)
print(df.head())

api.ohlcv(candle_duration_in_minutes = 1440) is a parameterized view (1440 = daily candles). close is a high-precision Decimal — cast it with toFloat64(close) before arithmetic.

The market symbol is quoted per venue: USD venues (Coinbase, Kraken, Bitstamp) publish BTC-USD; USDT venues (Binance, OKX, Bybit, KuCoin, Gate.io) publish BTC-USDT. These are different markets — to see BTC across all exchanges filter market IN ('BTC-USD', 'BTC-USDT').

3. First plot — average BTC price across all exchanges

import matplotlib.pyplot as plt

avg = df.groupby("start")["close"].mean()

avg.plot()
plt.title("Average BTC price across all exchanges (daily close)")
plt.ylabel("USD")
plt.show()

Next: browse Data, or use the REST option in How to connect.