The route from raw chain
to clean answers.
Four stages turn chain noise into something you can build on: ingest events live, structure them into typed tables, query in plain SQL, serve it to your users. We run the infrastructure for each stage.
Events arrive pushed, not polled.
Yellowstone gRPC on Solana, order-book websockets on Hyperliquid, gRPC on Monad — live events land in your pipeline as they happen, with no polling gaps to backfill later.
Base64 in, typed columns out.
Swaps, transfers, and balances normalized across 6 Solana DEX platforms — plus nanosecond-precise Hyperliquid trade history and Polymarket markets. A schema you read, instead of program logs you decode.
Plain SQL, analyst-speed.
Direct ClickHouse access — joins, CTEs, window functions your team already writes. 82 ms p99 on production queries; BI tools and notebooks connect out of the box.
From dataset to your product.
Live dashboards mix streams with SQL. Heavy backfills, custom schemas, or chains we haven't indexed yet get a scoped custom indexer or a dedicated node — built per order.
What data can I access through Supanode for analytics?
Normalized Solana DEX swaps across 6 platforms with token flows, holder distributions, and wallet PnL; complete Hyperliquid perpetual trading history with nanosecond-stamped fills; and Polymarket prediction-market history — about 1.35B order-fill events plus market and event metadata. All three are ClickHouse datasets queryable in plain SQL, and raw JSON-RPC plus live gRPC streams cover anything the indexers do not.
Do you offer indexed data or just raw RPC access?
Both. The indexers serve normalized, typed columns in ClickHouse for SQL analytics, while standard JSON-RPC handles raw on-chain reads and Yellowstone gRPC streams live events into ingestion pipelines. Many teams query the indexer for history and keep gRPC for the real-time tail.
How do I query Supanode indexed data?
Through direct ClickHouse SQL — joins, CTEs, and window functions — using clients like DBeaver, DataGrip, or psql. Supanode can also build a custom REST endpoint around a specific query if SQL is too low-level for a given team. Connection details are provisioned per customer over Telegram.
What Solana data is indexed and how fresh is it?
DEX swaps normalized across 6 platforms (Raydium, Meteora, Pump.fun, PumpSwap, LaunchLab, Letsbonk.fun), plus token holder counts, mints, burns, transfers, and wallet PnL history. Freshness is about 15 seconds from chain (p50 14s) with an 82 ms query p99, and historical coverage since 2024-01-11.
Can I get perpetual trading data for Hyperliquid?
Yes. The Hyperliquid indexer holds complete perpetual trading history — every fill, funding payment, and TWAP execution across all perpetual markets — each fill carrying a nanosecond timestamp for latency and order-flow analysis, in the same ClickHouse SQL interface.
Can I analyze multiple ecosystems from one provider?
Yes. The Solana, Hyperliquid, and Polymarket indexers run in the same ClickHouse SQL interface, so one set of tooling covers DEX activity, perpetual fills, and prediction-market history. Each dataset is provisioned with its own credentials over Telegram.
How do I feed real-time data into a live dashboard?
Yellowstone gRPC pushes accounts, transactions, slots, and blocks into your pipeline the moment they happen, with no polling gaps. For SQL-backed dashboards, the Solana indexer runs about 15 seconds behind chain with an 82 ms query p99 — fresh enough for monitoring panels without running a streaming consumer.
Will rate limits affect my data ingestion pipeline?
gRPC throughput is unlimited and unmetered, so streaming ingestion scales without a per-byte bill; the tier sets concurrent connections and per-stream filter width. Shared RPC plans publish per-tier RPS caps, and indexer queries are unlimited within tier limits. Backfills heavy enough to saturate a shared tier can run on a dedicated node, which has no rate limits.
Query the chain like a database.
Tables instead of base64, SQL instead of pagination. Tell us what you're building — we'll point you at the right datasets. Provisioning over Telegram with an engineer.