Analyzing Ethereum, Bitcoin, and 1200+ other Cryptocurrencies using PostgreSQL

Cryptocurrencies are fueling a modern day gold rush. Can data help us better understand this evolving market?
Lately it seems like money has been growing on trees.
With trade volumes reaching billions of dollars a day and market caps hitting tens of billions of dollars, it’s no wonder that cryptocurrencies fuel the gold rush of the modern day.

As we embrace this new, proliferous market, it’s important that we try to understand what’s going on. There are many risks to observe at both the micro-level (e.g., personal investments) and macro-level (e.g., prevention of market crashes and major loss of capital). That’s where we come in.

For this analysis*, we looked at historical OHLCV price data on over 1200 cryptocurrencies (as of 6/26/2017; courtesy of CryptoCompare). While our current dataset represents only a daily record of rates, TimescaleDB scales easily to much finer-grained historical data. With the constant influx of new coins and exchanges, TimescaleDB can provide a reliable foundation for time-series data in the cryptocurrency market.
Here’s what you should take away from this post:
Several high-level insights into the cryptocurrency market
A better understanding of how TimescaleDB + PostgreSQL make time-series data analysis easier
Instructions on how to load this dataset yourself and draw your own insights (and perhaps find your own arbitrage opportunities!)