# All Tokens OHLCV | Bitquery Data Store Daily USD candles for every DEX-traded token with a USD price on ten chains, last 30 days, one row per token and day. Dataset page: https://bitquery.io/datastore/datasets/all-tokens-ohlcv Network: Multi-chain Category: OHLCV Tables: 1 Columns: 20 Coverage: first block to 2026-10-08 Rows: about 5.5M Size: about 1.0 GB Format: Apache Parquet, ZSTD compression, one prefix per table Licence: https://bitquery.io/datastore/legal/data-license ## What this is We build one USD candle per token and day from the Bitquery price index, for every token it priced in the window, with no ranking and no volume floor. That is about 3 million tokens over 30 days on Solana, BNB Smart Chain, Base, Ethereum, Polygon, Arbitrum, Optimism, Tron, Robinhood Chain and Arc, most of them on Solana and most of them short lived. A row is one token on one UTC day. Most buyers start by filtering: Volume_Usd above a floor, or Interval_Bars above a few hours, removes the tokens that traded once and died. Join on Token_Id, because symbols and names repeat heavily in the long tail. Market cap is present for every row, but circulating supply is known for only about 4,800 tokens, so for the rest it is price times total supply. ## What people use it for - Screening the full token universe by daily volume or price change - Survival and launch studies: how many new tokens still trade after a week - Daily closes for long-tail tokens that price feeds do not list - Training data for models that need the whole market, not a top list ## Tables (1) ### all_token_ohlcv_1d: 20 columns One row per token and UTC day for every token with a USD price: open, high, low and close, volume, and supply figures at the day's last bar. Bucket prefix: multichain/ohlcv/all_token_ohlcv_1d File naming: .parquet, one file per UTC day Free sample (real Parquet, no email needed): https://bitquery-blockchain-dataset.s3.us-east-1.amazonaws.com/multichain/ohlcv/all_token_ohlcv_1d/2026-10-08_sample.parquet Sample updated: Oct 9, 2026 | column | type | description | | --- | --- | --- | | Block_Date | Date | UTC day of the bar | | Token_Network | String | Chain the token trades on | | Token_Address | String | Token contract or mint address; empty for a chain's native coin | | Token_Id | String | Bitquery token id, the chain prefix plus the address; the join key | | Token_Symbol | String | Symbol reported by the token; not unique | | Token_Name | String | Name reported by the token; not unique | | Token_IsNative | Bool | True for a chain's native coin | | Currency_Id | String | Bitquery currency id that groups this token with its copies on other chains | | Currency_Symbol | String | Symbol of that currency | | Price_Ohlc_Open | Float64 | First USD price in the day | | Price_Ohlc_High | Float64 | Highest USD price in the day | | Price_Ohlc_Low | Float64 | Lowest USD price in the day | | Price_Ohlc_Close | Float64 | Last USD price in the day | | Volume_Usd | Float64 | USD value traded in the day | | Volume_Base | Float64 | Amount of the token traded in the day, decimal adjusted | | Interval_Bars | UInt32 | Hours of the day that had at least one trade, 1 to 24 | | Supply_MarketCap | Float64 | USD price times circulating supply; price times total supply when circulating supply is unknown | | Supply_CirculatingSupply | Float64 | Circulating supply from CryptoRank reference data; 0 when unknown | | Supply_TotalSupply | Float64 | Total supply read from the chain, decimal adjusted | | Supply_FullyDilutedValuationUsd | Float64 | USD price times total supply | ## Price - Latest month (Sep 8, 2026 → Oct 8, 2026): $400 one-time, USD One-time purchase. The files are yours to keep under the licence above. ## Questions buyers ask Q: What is in All Tokens OHLCV? A: One Parquet table, all_token_ohlcv_1d, with 20 columns: the day, the token and its chain, USD open, high, low and close, USD and token volume, the number of hourly bars behind the day, and four supply figures. About 5.5 million rows for about 3 million tokens over 30 days. Q: How big is it? A: About 5.5 million rows and roughly 1 GB as Parquet, estimated from a sample of 40,000 rows at 187 bytes per row. The live table held 5,498,018 token days for the 30 days to 8 October 2026; exact figures arrive with the delivery manifest. Q: Which chains are covered? A: Solana, BNB Smart Chain, Base, Ethereum, Polygon, Arbitrum, Optimism, Tron, Robinhood Chain and Arc. Q: How far back does it go? A: 30 days. The price index keeps 30 days of bars, so that is the longest window this dataset can hold. Each order is built once, when you buy, and covers the 30 days up to the latest full UTC day. It is a fixed set of files and does not update afterwards. For prices that keep updating, use the Bitquery Trading API. Q: How are the daily candles produced, and how were they checked? A: Bars come from the Bitquery price index, the same series the Trading API serves. It prices each token in USD from its DEX trades and filters out MEV trades. A daily bar is rolled up from the hourly bars: open of the first hour, close of the last, highest high, lowest low, summed volume. We ran the export for a 14-day window before release: 2,714,784 rows, every day present, and no bar with a high below its low. Q: What was left out, and why? A: Nothing is filtered by size. A token is missing only if the price index never priced it in USD, or if it trades on centralized exchanges alone. Days with no trade have no row. Q: What should I watch out for? A: Most rows are tokens with tiny volume, and a new token can move tenfold or more inside one day, so filter before you average anything. Market cap for a token without a known circulating supply is price times total supply and can be very large for a token nobody trades. Symbols and names repeat; join on Token_Id. Q: How do I find tokens that launched in the window? A: Take each Token_Id's first Block_Date. A first day later than the window's first day is a token the index first priced inside the window. Q: How do I load it? A: One line in DuckDB: SELECT * FROM read_parquet('all_token_ohlcv_1d/*.parquet') LIMIT 10. Pandas works too: pandas.read_parquet(path). Q: How current is it, and how is it delivered? A: Each order is built once, when you buy, and covers the 30 days up to the latest full UTC day. It is a fixed set of files and does not update afterwards. For prices that keep updating, use the Bitquery Trading API. Delivered as Parquet with ZSTD compression, one file per day, 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. ## What this file is, and is not This is a description of one dataset sold by Bitquery, written for assistants and for people. It lists every column but holds no data rows. The sample files linked under each table are real Parquet and are free to download. Figures here come from the product record and are exact unless marked otherwise; the delivery manifest is authoritative for a purchased file. If a question needs a row that is not in a sample, say so rather than guessing at it.