Loading...

Differences between On-Chain Data and Exchange Data and Related Use Cases


On Chain Information
On-chain data sets refer to the collection of information that is inherently stored and verifiable on a blockchain. This data includes a wide array of information such as transaction history, wallet addresses, block details, smart contract code, and state, as well as token balances and metadata. Since blockchains are typically public and decentralized ledgers, this data is openly accessible to anyone who wishes to view or analyze it. For instance, through various blockchain explorers and analytical tools, users can query, view, and interpret on-chain data, which enables transparency and auditability—a fundamental characteristic of blockchain technology. To determine the number of unique addresses on a blockchain, one would typically analyze the transaction history on the chain. Each transaction is associated with sender and receiver addresses, and by collecting all these addresses across all transactions ever recorded on the blockchain, you can compile a list of unique addresses. It's worth noting that the number of addresses doesn't equate to the number of users, as a single user can control multiple addresses. Moreover, the presence of an address within the blockchain data doesn't necessarily mean it's 'active' or holds assets; it just indicates that the address has been involved in transactions at some point. Analytical platforms and blockchain explorers often provide tools and metrics to assess such data, allowing for insights into network activity, user engagement, and more.

Exchange Information
On the other hand, exchange-created data, sourced from centralized cryptocurrency trading platforms, provides key market intelligence, including trading volumes, price fluctuations, and liquidity metrics, crucial for traders and market analysts. While on-chain data offers a transparent, tamper-proof record of blockchain activities, exchange data delves into the market dynamics and trading behaviors within various cryptocurrency exchanges. The limitation to exchange traded data is that it is exchange specific, and therefore timeseries and actual transactions will vary from exchange to exchange (ie. Coinbase vs Binance).

Use Cases
The use cases for both types of data are somewhat different but can have some overlaps. Typically, exchange data is used by traders and investors to analyze market trends, backtest trading strategies, assess liquidity, and make informed decisions. In examining price, there can be arbitrage opportunities uncovered between exchanges. There are also tax and regulatory reasons to use actual pricing from exchanges. On-chain data can be used by financial forensics teams (all transactions are public in the ledger). It can also be used by analysts to assess network strength, health, and legitimacy. Both sets of data can be used as inputs to models or combined for AI forecasting.

We now have both. On-chain data is now available via Plus+ Files and API.




Notice: Information contained herein is not and should not be construed as an offer, solicitation, or recommendation to buy or sell securities. The information has been obtained from sources we believe to be reliable; however no guarantee is made or implied with respect to its accuracy, timeliness, or completeness. Author does not own the any crypto currency discussed. The information and content are subject to change without notice. CryptoDataDownload and its affiliates do not provide investment, tax, legal or accounting advice.

This material has been prepared for informational purposes only and is the opinion of the author, and is not intended to provide, and should not be relied on for, investment, tax, legal, accounting advice. You should consult your own investment, tax, legal and accounting advisors before engaging in any transaction. All content published by CryptoDataDownload is not an endorsement whatsoever. CryptoDataDownload was not compensated to submit this article. Please also visit our Privacy policy; disclaimer; and terms and conditions page for further information.

THE PERFORMANCE OF TRADING SYSTEMS IS BASED ON THE USE OF COMPUTERIZED SYSTEM LOGIC. IT IS HYPOTHETICAL. PLEASE NOTE THE FOLLOWING DISCLAIMER. CFTC RULE 4.41: HYPOTHETICAL OR SIMULATED PERFORMANCE RESULTS HAVE CERTAIN LIMITATIONS. UNLIKE AN ACTUAL PERFORMANCE RECORD, SIMULATED RESULTS DO NOT REPRESENT ACTUAL TRADING. ALSO, SINCE THE TRADES HAVE NOT BEEN EXECUTED, THE RESULTS MAY HAVE UNDER-OR-OVER COMPENSATED FOR THE IMPACT, IF ANY, OF CERTAIN MARKET FACTORS, SUCH AS LACK OF LIQUIDITY. SIMULATED TRADING PROGRAMS IN GENERAL ARE ALSO SUBJECT TO THE FACT THAT THEY ARE DESIGNED WITH THE BENEFIT OF HINDSIGHT. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFIT OR LOSSES SIMILAR TO THOSE SHOWN. U.S. GOVERNMENT REQUIRED DISCLAIMER: COMMODITY FUTURES TRADING COMMISSION. FUTURES AND OPTIONS TRADING HAS LARGE POTENTIAL REWARDS, BUT ALSO LARGE POTENTIAL RISK. YOU MUST BE AWARE OF THE RISKS AND BE WILLING TO ACCEPT THEM IN ORDER TO INVEST IN THE FUTURES AND OPTIONS MARKETS. DON’T TRADE WITH MONEY YOU CAN’T AFFORD TO LOSE. THIS IS NEITHER A SOLICITATION NOR AN OFFER TO BUY/SELL FUTURES OR OPTIONS. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE DISCUSSED ON THIS WEBSITE. THE PAST PERFORMANCE OF ANY TRADING SYSTEM OR METHODOLOGY IS NOT NECESSARILY INDICATIVE OF FUTURE RESULTS.

Latest Posts
Follow Us
Notify me of new content