Solana DEX Swaps to your warehouse

Land decoded Solana DEX trades into ClickHouse, BigQuery, Postgres, Kafka, or S3 via the swaps normalizer.

The swaps normalizer streams decoded Solana DEX trades into your warehouse as one unified table.

Why warehouse delivery

REST is great for live lookups, but every retention cohort, churn model, token analytics dashboard, and tax export lives in your data warehouse - not in HTTP responses. GoldRush streams Solana data continuously into customer-managed destinations with no ETL on your side.

Pipeline configuration

1. Create a pipeline

   In the GoldRush Platform, navigate to Manage Pipelines and click Create Pipeline. Name it solana-swaps.

2. Pick Solana + Swaps

   Choose Solana as the chain and Swaps as the data type.

3. Configure your destination

   Connect ClickHouse, BigQuery, Postgres, Kafka, S3/GCS/R2, SQS, or a Webhook. ClickHouse is recommended for high-volume analytical queries over swaps.

   destination:
     type: "clickhouse"
     url: "https://your-cluster.clickhouse.cloud:8443"
     user: "${CH_USER}"
     password: "${CH_PASSWORD}"
     database: "solana_swaps"
     batch_size: 5000
   
4. Optional: SQL transform

   Filter or reshape rows before they land. Example: keep only swaps over $100 of volume.

   transforms:
     swaps: >
       SELECT *
       FROM swaps
       WHERE volume_usd >= 100
   
5. Deploy

   Decoded swaps begin flowing within seconds.

Schema

Key columns of the swaps table include block_slot, block_time, tx_id, signer, pool_address, base_mint, quote_mint, base_amount, quote_amount, price_usd, volume_usd, protocol_name, and CPI attribution fields (outer_program, inner_program, instruction_type).

Sample analytical queries

Top tokens by 24h volume

SELECT
  base_mint,
  SUM(volume_usd) AS volume_24h
FROM swaps
WHERE block_time >= now() - INTERVAL 1 DAY
GROUP BY base_mint
ORDER BY volume_24h DESC
LIMIT 50;

Per-protocol market share by token

SELECT
  protocol_name,
  SUM(volume_usd) AS volume_24h,
  COUNT(*) AS swap_count
FROM swaps
WHERE base_mint = 'EPjFWdd5AufqSSqeM2qN1xzybapC8G4wEGGkZwyTDt1v'
  AND block_time >= now() - INTERVAL 1 DAY
GROUP BY protocol_name
ORDER BY volume_24h DESC;

Whale activity

SELECT
  signer,
  SUM(volume_usd) AS volume_24h,
  COUNT(*) AS swap_count
FROM swaps
WHERE block_time >= now() - INTERVAL 1 DAY
GROUP BY signer
HAVING volume_24h > 1000000
ORDER BY volume_24h DESC;

Jupiter routing through Raydium and Orca

SELECT
  tx_id,
  protocol_name,
  outer_program,
  inner_program,
  base_mint,
  quote_mint,
  volume_usd
FROM swaps
WHERE outer_program = 'JUP6LkbZbjS1jKKwapdHNy74zcZ3tLUZoi5QNyVTaV4' -- Jupiter v6
  AND block_time >= now() - INTERVAL 1 HOUR
ORDER BY tx_id, instruction_index;

Production tips

• ClickHouse for high-volume analytics. Solana swap volume is significant; analytical queries over millions of rows are much faster on ClickHouse than Postgres.
• Partition by block_date. Most analytical queries are time-bounded.
• Materialized views for per-token metrics. Build hourly / daily roll-ups in ClickHouse materialized views to keep dashboards snappy.

Related

• SPL Transfers warehouse recipe - companion table for transfer-side analytics.