Polygon Transfers

One Parquet table with 24 columns: every native POL and token transfer on Polygon, one row each, with the amount, the token's details, the transaction it settled in and the fee. POL moved by contracts in internal calls is included, and so are NFTs.

About 28.7 billion rows over 77 months, roughly 780 GB as Parquet, estimated from the sample files. The last 24 months hold about 19.3 billion rows and the last 12 months about 15.0 billion. Row counts come from the live table; exact figures arrive with the delivery manifest.

To the start of indexed history: from 30 May 2020, at block 447, the first block with a transfer. The Full window runs from there to yesterday.

The export applies no filter of its own: spam tokens, lookalike tokens, zero-value rows and failed transactions all stay in, and the columns let you drop them. Value credited outside a transaction or a contract call has no row, the genesis allocation for one, so check native POL balances rebuilt from these rows against the chain. Token balances hold, rebasing tokens aside.

Only six currencies have a price history on Polygon: POL (formerly MATIC), WPOL, WETH, USDT, DAI and the bridged USDC.e. Circle's native USDC has no series yet. In a recent six-hour window that priced about 22% of rows; the rest is mostly airdrop and spam tokens. The free sample was priced from a wider short-term source, so half its rows show a USD value, more than a delivered file will. A value of 0 means either a $0 transfer or no price; the column cannot tell them apart.

Decoded from Polygon by our own indexer, which reads token transfer events and traces internal calls for POL. Before release we read the sample back: 34,525 rows over blocks 82,133,800 to 82,133,849, every amount carrying exactly its token's decimals. The live table returns the same 34,525 rows for those blocks.

The amount column is decimal adjusted. Multiply it by 10 to the power of the token's decimals for the raw on-chain integer. We ship the adjusted value because decimals differ per token and the raw figure is wrong without them.

Amounts are decimal strings, so casting to float loses precision on large values. Symbols and names repeat, and lookalike tokens copy them, so join on the contract address. Failed transactions are kept; filter TransactionStatus_Success for settled flow. Zero-value rows, 0.3% of the sample, move nothing, so drop them before counting activity. Every native POL row is marked call in Transfer_Type, a plain send included. The S3 prefix is matic/transfers, the chain's name before the rebrand to POL.

Filter Transfer_Currency_SmartContract to the token's contract, lower case with 0x. For native POL alone, filter Transfer_Currency_Native to true; its contract column holds the string 0x. The files still label native rows MATIC, so a filter on the symbol POL finds nothing.

One line in DuckDB: SELECT * FROM read_parquet('transfers/*.parquet') LIMIT 10. Pandas works too: pandas.read_parquet(path). The sample file opens without credentials.

Refreshed daily with T+1 latency, so a purchase made today includes everything to yesterday. Delivered as Parquet named by block range, 50 blocks per file and sorted ascending, under a stable layout with a JSON manifest listing every file and its sha256. We prepare the files within 7 business days of purchase and email you the location. 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. Enterprise orders can be delivered into your own S3, GCS or R2 bucket.