2024 was a major year for cryptocurrency markets. Bitcoin completed another halving, spot Bitcoin ETFs expanded institutional access in the U.S., and Bitcoin crossed $100,000 for the first time in December.
Political and macroeconomic events also continued to influence crypto markets, reinforcing just how quickly sentiment, liquidity, and volatility can change.
For institutions entering crypto in 2025, access to data is becoming increasingly important. Trading firms, developers, researchers, and financial institutions need normalized real-time feeds and high-resolution historical datasets for trading, research, reporting, risk management, and increasingly… AI.
Here is what you need to know about crypto market data in 2025.
Who Needs Crypto Market Data in 2025??
The number of organizations working with digital assets continues to expand.
- Platform developers need historical and real-time data for trading terminals, portfolio trackers, wallets, analytics platforms, and other FinTech products.
- Financial institutions and trading firms use trades, quotes, order books, and historical datasets for market monitoring, quantitative research, backtesting, and risk management.
- Market makers and brokers require detailed market information to understand liquidity, spreads, and market conditions across venues.
- Researchers and universities use historical datasets to study market structure, volatility, correlations, and crypto market behavior.
- AI and machine-learning teams need large, consistent datasets for training, testing, feature engineering, and evaluating financial models.
Coverage varies by exchange, instrument, and data type, so organizations should always verify that their required venues and symbols are available.
Who Provides Crypto Market Data?
Market data can be collected directly from exchanges.
However, exchange APIs differ significantly. Some provide extensive historical data, while others have limited history, different schemas, rate limits, naming conventions, or different levels of reliability.
This becomes increasingly difficult when an application needs dozens or hundreds of venues.
In 2025, CoinAPI provides normalized crypto market data from 400+ integrated exchanges, allowing users to access multiple markets through standardized interfaces rather than maintaining individual exchange integrations.
What are the main types of market data?
There are a lot of data types to track. Here are some of them:
- Quotes: Real-time bid and ask prices for cryptocurrency pairs.
- Trades: Detailed information about individual transactions, including price, volume, and timestamp.
- Limit Book Snapshots: Snapshots of the current state of the order book, displaying available buy and sell orders at various price levels.
- Full Limit Order Book: A comprehensive view of all active buy and sell orders in the order book.
- OHLCV (Open, High, Low, Close, Volume): Aggregated data that summarizes the price movements and trading volume over specific time intervals.
- Index Data: Composite metrics that measure the performance of a basket of assets or specific market segments.
- Futures and Derivatives
- Funding Rates: Data on regular funding rates applied to open positions to maintain price parity with the underlying asset.
- Open Interest: Metrics reflecting the total number of outstanding derivative contracts.
- Mark Price: Fair price calculations used to prevent unnecessary liquidations.
- Liquidation Data: Information on positions that have been forcefully closed due to insufficient margin.
- Position Data: Aggregated long/short ratios and position sizes
- Spreads: Price differences between related instruments
- Swaps: Interest rate and total return swap data
- Options: Put/call ratios, strike prices, and implied volatility
How is cryptocurrency data aggregated and standardized?
One of the biggest challenges in crypto is that exchanges describe similar market events differently.
Identifiers, timestamps, symbols, schemas, and order book formats can all vary.
CoinAPI collects market events and reference data from supported venues and normalizes them into common schemas. This includes standardized exchange IDs, asset IDs, symbol IDs, timestamps, trades, quotes, order books, and OHLCV data.
This makes it easier to compare markets and build systems that work across multiple exchanges.
Importantly, this normalization should not be confused with index or reference-rate calculation.
Methodologies such as VWAP and PRIMKT involve additional aggregation and calculation rules. They are part of products such as CoinAPI Indexes API rather than the basic process of normalizing individual exchange events.
What is the key difference between obtaining real-time and historical data?
The difference is not simply which connection is used. Real-time and historical datasets are optimized for different jobs.
Real-Time Market Data
For continuous real-time feeds, WebSocket is generally the most practical interface. It maintains an active connection and delivers updates as market events arrive.
FIX is also available for institutional market-data infrastructure.
REST can provide latest snapshots or periodic polling, but WebSocket and FIX are better suited to continuous streaming.
Historical Market Data
REST is useful when applications need request-response access to specific historical periods. Performance depends on the dataset, query size, symbols, payload, network, and other factors.
For large historical workloads, Flat Files provide bulk datasets through S3-compatible access, including trades, quotes, order books, and OHLCV where available.
Historical datasets can also undergo additional quality processing after collection, including deduplication and reconciliation of late or out-of-order events.
That makes finalized historical data especially valuable for reproducible backtesting, quantitative research, and machine learning.
| Requirement | Best Fit |
| Current or targeted historical queries | REST API |
| Continuous real-time market data | WebSocket |
| Institutional market-data workflows | FIX |
| Bulk historical research and backtesting | Flat Files |
There is also an important distinction between market data and execution.
CoinAPI Market Data FIX is used for market-data delivery. Order routing, balances, positions, and execution workflows belong to the EMS Trading API.
How is crypto data typically priced and licensed?
Crypto data pricing typically depends on the product, volume of data consumed, API usage, and service requirements.
CoinAPI currently offers Pay As You Go, committed plans, and Enterprise options, with new users receiving $25 in free credits for testing.
Licensing is equally important.
Internal research and backtesting are different from redistributing raw market data or displaying it to external customers. Raw data redistribution, public display, and commercial sublicensing may require specific licensing rights.
Derived-data applications should also be reviewed according to the intended use.
Enterprise customers with specific infrastructure, support, or SLA requirements can discuss those requirements directly with CoinAPI.
Crypto Market Data Trends to Watch in 2025
Institutional Adoption
Institutional participation remains one of the most important forces shaping the crypto market.
Spot Bitcoin ETFs have expanded regulated access to Bitcoin, while trading firms, asset managers, banks, and FinTech companies continue exploring digital-asset products.
That increases demand for standardized market data, historical datasets, reference rates, and risk infrastructure.
AI and Machine Learning
AI is also changing how organizations use crypto data.
Machine-learning teams can use historical trades, quotes, OHLCV, and order books for feature engineering, market-regime analysis, anomaly detection, forecasting research, and strategy development.
But AI does not fix weak data.
Duplicate events, missing history, inconsistent symbols, and poorly reconstructed order books can directly affect model quality. For AI workflows, clean historical data is becoming just as important as model architecture.
Low-Latency Infrastructure
As quantitative and automated trading grows, latency remains important.
WebSocket and FIX support continuous market-data delivery, while specialized enterprise connectivity can be considered when applications have stricter infrastructure and latency requirements.
Better Historical Data
Historical data is no longer needed only for charts.
Quantitative researchers increasingly need detailed trades, quotes, and order books to reconstruct market conditions, test execution models, train ML systems, and analyze liquidity.
For these use cases, bulk historical delivery through Flat Files can be more practical than retrieving large datasets request by request.
Building With Crypto Market Data in 2025
The crypto market is becoming more institutional, more automated, and more data-intensive.
For developers and financial institutions, the challenge in 2025 is not simply accessing a cryptocurrency price. It is obtaining consistent data across venues, understanding its history, selecting the right delivery method, and making sure the dataset is suitable for the system being built.
For real-time and historical API access, explore the CoinAPI Market Data API.
For large historical datasets used in backtesting, quantitative research, and machine learning, explore CoinAPI Flat Files.
Create your account and get $25 in credits to start testing CoinAPI products. Explore real-time Market Data APIs, access bulk historical datasets through Flat Files, or manage your API keys, Usage Credits, and subscriptions directly from the APIBricks Console.
Related Topics
- What Is Level 4 (L4) Order Book Data?
- CoinAPI Introduces Hyperliquid L4 Data
- Building a Reproducible Hyperliquid Order Book Replay from CoinAPI Book L4 Flat Files
- What Data Is Available Through CoinAPI WebSocket DS for Hyperliquid?
- Demystifying Level 4 (L4) Order Book Data: Why Waiting for Block Confirmations Is Dead on Arrival
- Crypto Data Quality Checklist
- Tokenized Stocks Are Here. Should We Pay Attention?
