#Datachain

Datachain is a flexible, lightweight and customizable python library for interoperable access of data from underlying blockchains.

Datachain Model

Datachain adopts a CRAB (Create-Retrieve-Append-Burn) approach from data management, which is inherent to the basic blockchain principles.

The Datachain model provides CRAB operations for the following:

• Participants
• Assets with immutable and associated data. Multiple asset types as well.
• Transactions... multiple transaction types as well.

Datachain Data Formatting

Data extracted from underlying blockchains can be retrieved as:

• In raw format, meaning exactly as returned from the underlying blockchain.
• In xml format.
• In json format.
• As a collection. Depending on the request this may be a dictionary, list or tuple.
• As a pandas.Series for 1d or pandas.DataFrame for 2d data. By simply requesting pandas the default response is a DataFrame.

Supported Blockchains

Currently, Datachain provides under-the-hood connectors for:

• BigchainDB apps
• Hyperledger Composer apps

Prerequisites

Datachain requires a python3 version (tested on v3.7.x). Other required libraries are: numpy, pandas, and dicttoxml.

To use the BigchainDB connector, the bigchaindb_driver is required.

Reference

When using the framework please use the following reference to cite our work:

Demetris Trihinas. 2019. Datachain: A Query Framework for Blockchains. In Proceedings of the 11th International Conference on Management of Digital EcoSystems (MEDES ’19). Association for Computing Machinery, New York, NY, USA, 134–141. DOI:https://doi.org/10.1145/3297662.3365796