Solana DEX Swaps to your warehouse - GoldRush API Documentation

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.

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.

Pipeline configuration

Create a pipeline

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

Pick Solana + Swaps

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

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

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

Deploy

Decoded swaps begin flowing within seconds.

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).

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;

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.

Solana Normalizers (full schema) - column-level reference for swaps and other Solana entities.
SPL Transfers warehouse recipe - companion table for transfer-side analytics.
DEX firehose (streaming) - real-time push for new pair events.

​Why warehouse delivery

​Pipeline configuration

​Schema

​Sample analytical queries

​Top tokens by 24h volume

​Per-protocol market share by token

​Whale activity

​Jupiter routing through Raydium and Orca

​Production tips

​Related