HyperliquidEventsHourly HyperCore funding payments: one row per account, market and settlement, with the rate, signed position size and USDC paid or received.
perp_fundingsHyperliquid funding data from the HyperCore L1, not HyperEVM. HyperCore settles funding once an hour, and the perp_fundings table has one row per account and market at each settlement: the hourly rate, the signed position size it applied to, and the USDC amount paid or received. One settlement block on 29 September 2026 held 411,880 rows across 327 markets.
Funding_Amount is negative when the account paid and positive when it received, and Funding_Size is negative for a short, so the sign of every payment can be checked against the rate. Amounts, rates and sizes are decimal strings, addresses are 0x-prefixed hex, and Block_Time is epoch nanoseconds.
One row per account and market at each hourly funding settlement: the rate, the signed position size it applied to, and the USDC paid or received.
hyperliquid/perp_fundings<start_block>_<end_block>.parquet200 blocks per fileSend this dataset’s full schema to an assistant and ask it anything. It reads the plain-text brief first, so the answer comes from the real column list rather than a guess.
Opens a new chat with the question filled in. Nothing about you is sent to Bitquery, and the assistant sees only the public brief.
Parquet files in a Requester Pays S3 bucket or a Cloudflare R2 bucket, chosen at checkout. On S3 you download with your own AWS account and AWS bills the transfer; on R2 you download with a read-only API key and pay no egress. Layout:
# perp_fundings: 200 blocks per file
hyperliquid/perp_fundings<start_block>_<end_block>.parquetperp_fundings table, 23 columnsOne Parquet table from HyperCore, perp_fundings, with 23 documented columns. Each row is one hourly funding payment for one account and market. Every row carries Block_Number and Block_Time, so it joins on block with the Hyperliquid Trades and Order Book datasets.
In September 2026 our live tables held 7.9 to 9.9 million funding rows a day from 24 hourly settlements, paid by 130,000 to 160,000 accounts across 314 to 329 markets. That is roughly 270 million rows for 30 days, and one settlement block is about 11 MB of Parquet, so around 8 GB in total. These figures are estimates; exact row counts and sizes come with the delivery manifest.
Funding_Amount is the USDC the account received, negative when it paid, and Funding_Size is the signed position, negative for a short. With a positive Funding_Rate, longs pay shorts: in one day of September 2026 data, 99.7% of long positions under a positive rate had a negative amount.
Filter on Funding_Trader_Address and sum Funding_Amount, grouped by Funding_Market_CoinRaw for a per-market view. Each row is one settlement, so the sum over a window is the net funding for that window.
Funding_Trader_Signer, Funding_Trader_Vault, Funding_Trader_Broadcaster and Funding_Trader_SignedAt are always empty, because the chain settles funding and no account signs it. They are part of the shared Hyperliquid schema. Funding_Market_MaxLeverage is filled when our export can read market metadata and can be 0.
Ledger events such as deposits, withdrawals, sends, transfers and vault flows, bridge and staking events, and CoreWriter actions from HyperEVM. Our export does not produce those tables yet. Fills are in the Hyperliquid Trades dataset.
30 days. HyperCore history is kept as a rolling 30-day window, so a purchase covers the 30 days up to the day before we prepare the files, and there is no longer window to buy. For a continuous feed beyond that, ask about the live stream.
With DuckDB: SELECT * FROM read_parquet('perp_fundings/*.parquet'). With pandas: pd.read_parquet('perp_fundings/'). Parse Funding_Amount, Funding_Rate and Funding_Size with Decimal rather than float; they are stored as decimal strings on purpose.
Yes. These field definitions are the ones Bitquery's Hyperliquid Kafka topics use, so a backtest reading this archive and a production consumer reading the live stream decode with the same code.
As flat Parquet files under a stable layout, one prefix per table and one file per 200-block range, with a JSON manifest listing every file and its sha256. We prepare the files within 7 business days of purchase, covering the 30 days up to the day before. You choose at checkout where to collect them: a Requester Pays S3 bucket, downloaded with your own AWS account, or a Cloudflare R2 bucket with a read-only API key and no egress fees. Files stay available for 7 days from delivery.
Yes. The table links to a public sample Parquet file with the first 100 rows of a real settlement block and every column the export writes. The sample repository on GitHub shows the first records as readable JSON. No email address required.
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