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The swaps normalizer streams decoded Solana DEX trades into your warehouse as one unified table. See the Solana normalizers page for the full per-column schema and supported protocols.

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Why warehouse delivery

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

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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.

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Schema

The swaps table is documented in full on the Solana Normalizers page. Key columns 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).

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Sample analytical queries

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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;

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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;

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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;

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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;

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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.