The financial industry is extremely data-heavy and relies on real-time and historical data for decision-making, risk assessment, fraud detection, and market analysis. Timescale simplifies management of these large volumes of data, while also providing you with meaningful analytical insights and optimizing storage costs.
In this tutorial, you use Timescale to ingest, store, and analyze transactions on the Bitcoin blockchain.
Blockchains are, at their essence, a distributed database. The
transactions
in a blockchain are an example of time-series data. You can use
Timescale to query transactions on a blockchain, in exactly the same way as you
might query time-series transactions in any other database.
Before you begin, make sure you have:
- Signed up for a free Timescale account.
This tutorial covers:
This tutorial uses a sample Bitcoin dataset to show you how to construct queries for blockchain data. The queries you do in this tutorial is used to do things like determine if a cryptocurrency is performing as expected, graph currency values over time, and compare currencies.
It starts by teaching you how to set up and connect to a Timescale database,
create tables, and load data into the tables using psql
.
You then learn how to conduct analysis on your dataset. It walks you through using PostgreSQL queries to obtain information, including finding the most recent transactions on the blockchain, and gathering information about the transactions using aggregation functions.
When you've completed this tutorial, you can use the same dataset to complete the advanced blockchain tutorial, which shows you how to analyze the blockchain data using Timescale hyperfunctions.
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