September 29, 2025

OHLCV Data Now Available in CoinAPI Flat Files

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The cryptocurrency markets operate around the clock, across hundreds of exchanges, and at incredible speed. For serious participants like quantitative traders, algorithm developers, AI teams, researchers, compliance officers, and data-driven platforms, high-quality OHLCV data is the backbone of analysis and decision-making.

We are pleased to confirm that OHLCV (Open, High, Low, Close, Volume) data is now available in CoinAPI Flat Files, alongside trades, quotes, and full limit order book data. This release provides users with reliable, time-bucketed candlestick data that is normalized, reproducible, and ready for large-scale crypto data download.

OHLCV data aggregates raw trades into fixed intervals, creating a structured view of market behavior:

  • Open: the first traded price in the period
  • High: the highest price reached
  • Low: the lowest price recorded
  • Close: the last traded price
  • Volume: the total traded amount during the interval

This candlestick format allows us to:

  • Build visualizations for trading dashboards
  • Calculate technical indicators such as moving averages, RSI, or Bollinger Bands
  • Backtest and validate strategies over years of historical data
  • Train machine learning and AI models with structured, gap-free time series
  • Standardize reporting, compliance checks, and risk monitoring

Without accurate OHLCV coverage, market insights risk becoming incomplete or misleading.

→ For more context on how OHLCV candles are structured and applied in crypto markets, see our guide on understanding OHLCV in market data analysis.

CoinAPI delivers OHLCV in S3-organized CSV files compressed with gzip, ensuring efficiency for storage and ingestion.

Directory structure:

1T-OHLCV_ACTIVE_CONSOLIDATED/
2└── D-YYYYMMDD/
3    └── E-[EXCHANGE]/
4        ├── TP-1SEC.csv.gz
5        ├── TP-1MIN.csv.gz
6        ├── TP-1HRS.csv.gz
7        └── TP-1DAY.csv.gz
8
  • T-OHLCV_ACTIVE_CONSOLIDATED = Data type and consolidated feed identifier
  • D-YYYYMMDD = Date in UTC
  • E-[EXCHANGE] = Exchange identifier such as BINANCE, BITSTAMP, or KRAKEN
  • TP-<TF>.csv.gz = Timeframe of the candles (1 second, 1 minute, 1 hour, 1 day)

Each file contains all symbols listed on that exchange for the date, making the workflow predictable and scalable.

Below is a sample of 1-day candles for BITSTAMP on 2025-09-11 (first 3 rows):

1symbol_id;time_period_start;time_period_end;time_open;time_close;px_open;px_high;px_low;px_close;sx_cnt;sx_sum
228962;2025-09-11T00:00:00.0000000;2025-09-12T00:00:00.0000000;2025-09-11T00:09:59.0940000;2025-09-11T23:45:34.4680000;0.00002616;0.0000266;0.00002601;0.00002637;336;311129.52253198996
35960616;2025-09-11T00:00:00.0000000;2025-09-12T00:00:00.0000000;2025-09-11T02:46:38.1600000;2025-09-11T22:16:12.4040000;0.67731;0.69377;0.67718;0.69105;20;18599.91622281
45960615;2025-09-11T00:00:00.0000000;2025-09-12T00:00:00.0000000;2025-09-11T00:29:40.4330000;2025-09-11T23:20:56.9470000;0.78654;0.82999;0.78654;0.82999;31;33858.573104519994
55968362;2025-09-11T00:00:00.0000000;2025-09-12T00:00:00.0000000;2025-09-11T16:09:43.3500000;2025-09-11T16:09:43.3500000;1;1;1;1;1;100.28572
65968363;2025-09-11T00:00:00.0000000;2025-09-12T00:00:00.0000000;2025-09-11T01:18:29.7080000;2025-09-11T23:30:14.6410000;2.98968;3.05083;2.98968;3.05083;6;1474.43175271
75968361;2025-09-11T00:00:00.0000000;2025-09-12T00:00:00.0000000;2025-09-11T00:00:09.6540000;2025-09-11T23:44:15.7310000;0.85437;0.85686;0.85175;0.85223;1752;1368206.4252600016
85968795;2025-09-11T00:00:00.0000000;2025-09-12T00:00:00.0000000;2025-09-11T04:05:05.5740000;2025-09-11T17:21:32.2170000;0.08388;0.08467;0.08387;0.08428;7;6664.761867159999
95968794;2025-09-11T00:00:00.0000000;2025-09-12T00:00:00.0000000;2025-09-11T03:23:49.8240000;2025-09-11T22:20:17.6040000;0.09855;0.09957;0.09676;0.09957;7;55950.288868229996
105985325;2025-09-11T00:00:00.0000000;2025-09-12T00:00:00.0000000;2025-09-11T11:23:24.2080000;2025-09-11T22:52:41.6570000;0.64582;0.70424;0.64582;0.7;5;2464.8122367
115968562;2025-09-11T00:00:00.0000000;2025-09-12T00:00:00.0000000;2025-09-11T02:36:45.0320000;2025-09-11T23:19:12.7730000;37.93;38.64;37.62;38.64;11;4.57320563

→ If you are using this data to visualize trends, our article on how to read crypto candlestick charts using OHLCV data will help you interpret patterns correctly.

Flat Files are ideal for bulk crypto data download and long-term reproducibility. But CoinAPI also makes OHLCV available through the Market Data API, giving you flexibility for live and on-demand workflows:

  • REST API – fetch historical OHLCV series programmatically, with precise control over symbols, periods, and time ranges (1SEC → 1DAY)
  • WebSocket API – stream OHLCV updates in real time without polling, perfect for dashboards and live trading systems
  • FIX API – institutional desks can consume OHLCV via FIX, alongside trades and order book data

→ We also cover how to work with OHLCV streams in real time in OHLCV Data Explained: Real-Time Updates, WebSocket Behavior & Trading Applications.

→ Not sure whether to use bulk files or API queries? Read our comparison on REST API or Flat Files: Choosing the best crypto data access method.

CoinAPI maintains one of the largest coverage footprints in the industry:

  • 632 TB of historical market data
  • 380+ integrated exchanges
  • 599,000+ symbols tracked

This scale provides:

  • Multi-exchange backtesting without blind spots
  • Cross-venue analysis for arbitrage, liquidity, and spreads
  • Reduced data cleaning time due to normalization and symbol mapping
  • Combined strength of bulk history and live updates in one workflow

Other providers may offer CSVs for a single exchange or limited on-chain feeds. CoinAPI delivers a unified and reproducible dataset across venues and time horizons.

→ OHLCV is only one layer of market data. Learn the differences between trades, quotes, and book data in Tick Data vs Order Book Snapshots: Complete Guide for Crypto Trading Systems.

Quant traders and hedge funds can run faster, cleaner backtests without worrying about rate limits, validating strategies with years of candles.

Algo developers and trading bot builders can train and optimize models using complete OHLCV histories, syncing data in bulk without throttling.

Machine learning and AI teams gain access to structured, gap-free candlestick data essential for predictive analytics and signal generation.

Academic researchers and PhD students can publish reproducible studies using a single, consistent dataset across multiple exchanges.

Risk, compliance, and reporting teams can rely on standardized candles for valuation models and maintain a clear audit trail without stitching data from multiple venues.

Crypto analytics platforms and dashboards can integrate bulk OHLCV into reliable charting and visualization tools.

Quants looking to validate models will benefit from Backtest Crypto Strategies with Real Market Data (Not Just OHLCV Charts).

For a full breakdown of how OHLCV fits into the wider data stack, see Understanding Crypto Market Data: From Tick Trades to OHLCV and Order Books.

ProviderAccess MethodsCoverageGranularityProsLimitations
CoinAPIFlat Files (S3), REST API, WebSocket, FIX, Snowflake380+ exchanges, 599k+ symbols, 632 TB+ historical data1 second to 1 dayBulk + streaming, normalized symbols, audit-ready, flexible accessPaid, requires infrastructure for large downloads
KrakenCSV/ZIP downloadsOnly Kraken markets1m, 5m, etc.Free, simple accessSingle venue, updated quarterly, no streaming
CoinGeckoAPI (CSV/JSON), chart exportsOn-chain pools, top tokens1s (on-chain) to 1dEasy, free, simple integrationRate limits, no deep exchange coverage
AmberdataREST, S3, Snowflake, DatabricksBroad, depends on contract1m+Strong for enterprise data lakesCostly enterprise contracts
Open datasets (GitHub, OpenDataBay)CSVSingle assets (e.g., BTC)1m–1hFree, research-friendlyIncomplete, not normalized, no live feed

Q1: When are OHLCV Flat Files published each day?

Files are generated after 00:00 UTC for the previous day. Most are available by 06:00 UTC, with lighter datasets often ready within a few hours after midnight.

Q2: How far back does the OHLCV history go?

It depends on the asset and venue, but coverage is much deeper than 1–5 years for major pairs:

  • BTC spot pairs on top venues: 1-minute OHLCV back to 2010–2011 (10+ years)
  • ETH: generally from 2015
  • Altcoins: from their first exchange listings (varies by symbol/venue)

To check a specific symbol:

1GET /v1/ohlcv/BINANCE_SPOT_BTC_USDT/history?period_id=1MIN&time_start=2010-01-01T00:00:00Z&limit=1

Or review Metadata Tables for earliest available times.

Q3: How do I programmatically download OHLCV Flat Files?

Use any S3-compatible client. For example, with AWS CLI:

1aws --endpoint-url http://s3.flatfiles.coinapi.io s3 cp s3://coinapi/T-OHLCV_ACTIVE_CONSOLIDATED/D-20250911/E-BITSTAMP/TP-1DAY.csv.gz .

For Python, use boto3 or requests to script downloads and decompression.

Q4. How does CoinAPI compare to other OHLCV data sources

Most exchanges (like Kraken) only offer CSVs for their own markets. Free APIs (like CoinGecko) provide limited history and rate-limited access. Open datasets often cover just Bitcoin or a few assets. CoinAPI combines all three strengths: multi-venue coverage, bulk downloads, and real-time feeds.

  • OHLCV is now included in CoinAPI Flat Files, alongside trades, quotes, and order books.
  • Data is structured, normalized, and UTC aligned, ready for research and production systems.
  • Users can access data via Flat Files, REST API, WebSocket, FIX, and Snowflake.
  • CoinAPI delivers 632 TB of historical data across 380+ exchanges and 599k+ symbols.
  • Flat Files support large-scale crypto data download, while APIs handle live and flexible access.
  • Coverage outperforms competitors by combining bulk history and real-time feeds.

The addition of OHLCV data in CoinAPI Flat Files gives traders, researchers, and compliance teams a reliable way to work with reproducible crypto history. Normalized symbols, precise timestamps, and wide exchange coverage remove the usual pain points of fragmented feeds and missing candles.

You can now backtest across a decade of BTC history, train AI models, or keep an audit-ready archive without worrying about throttled APIs.

Explore the OHLCV documentation and download a data sample to get started.

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