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Getting Started

Connect to the Solana indexer in under 5 minutes.

1. Get Credentials

Request access or message @inventandchill.

You'll receive:

  • Host: 157.90.130.44
  • Port: 8123
  • Username and password

2. Choose Your Client

Option A: DBeaver (GUI)

Best for exploration and ad-hoc queries.

  1. Download DBeaver Community (free)
  2. Create new connection → Select ClickHouse
  3. Enter credentials:
FieldValue
Host157.90.130.44
Port8123
Username(your username)
Password(your password)
  1. Click Test Connection → Finish

You'll see all tables in the left panel. Double-click to browse data.

Tip: Right-click a table → Generate SQL → DDL to see the schema.

Option B: Python

Best for analysis and automation.

pip install clickhouse-connect pandas
import clickhouse_connect
 
client = clickhouse_connect.get_client(
    host='157.90.130.44',
    port=8123,
    username='your_user',
    password='your_pass'
)
 
# Query to DataFrame
df = client.query_df("""
    SELECT *
    FROM raydium_all_swaps
    ORDER BY block_time DESC
    LIMIT 100
""")
 
print(df.head())

Option C: HTTP API

For scripts and integrations.

# Simple query
curl 'http://157.90.130.44:8123/' \
  -u 'user:password' \
  -d 'SELECT count(*) FROM raydium_all_swaps'
 
# JSON output
curl 'http://157.90.130.44:8123/?default_format=JSON' \
  -u 'user:password' \
  -d 'SELECT * FROM raydium_all_swaps LIMIT 5'

3. Run Your First Query

-- What's happening right now?
SELECT
    block_time,
    'raydium' as source,
    base_coin,
    quote_coin_amount / 1e9 as sol_amount
FROM raydium_all_swaps
WHERE block_time > now() - INTERVAL 5 MINUTE
ORDER BY block_time DESC
LIMIT 10

Tips for Efficient Queries

Always Filter by Time

Tables are partitioned by date. Time filters dramatically speed up queries.

-- Fast: uses partition pruning
WHERE block_time > today() - 7
 
-- Slow: scans everything
WHERE signing_wallet = '...'

Use LIMIT During Exploration

-- See what's in a table
SELECT * FROM pumpfun_all_swaps LIMIT 100
 
-- Check column types
DESCRIBE pumpfun_all_swaps

Aggregate Before Joining

-- Good: aggregate first
WITH daily_volume AS (
    SELECT toDate(block_time) as date, sum(amount) as vol
    FROM swaps GROUP BY date
)
SELECT * FROM daily_volume WHERE vol > 1000000
 
-- Bad: join then aggregate on huge tables

Next Steps