ISSN :2582-9793

A journey towards the most efficient state database for Hyperledger Fabric

Original Research (Published On: 22-Oct-2023 )
A journey towards the most efficient state database for Hyperledger Fabric

Vladimir Gorgadze, Artem Barger and Ivan Laishevskiy

Adv. Artif. Intell. Mach. Learn., 3 (4):1526-1556

Vladimir Gorgadze : Moscow Institute of Physics and Technology

Artem Barger : IdeaDLT

Ivan Laishevskiy : ChainLabs

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Article History: Received on: 23-May-23, Accepted on: 15-Oct-23, Published on: 22-Oct-23

Corresponding Author: Vladimir Gorgadze

Email: vladimir.gorgadze@phystech.edu

Citation: Ivan Laishevskiy, Artem Barger, Vladimir Gorgadze (2023). A journey towards the most efficient state database for Hyperledger Fabric. Adv. Artif. Intell. Mach. Learn., 3 (4 ):1526-1556


Abstract

    

Hyperledger Fabric is a leading permissioned
blockchain platform known for its flexibility and customization.
A crucial yet often overlooked component is its state database,
which records the current state of blockchain applications. While
the platform currently supports LevelDB and CouchDB, this
study argues that there is an unmet need for exploring alternative
databases to enhance performance and scalability. We evaluate
RocksDB, Boltdb, and BadgerDB under various workloads,
focusing on memory and CPU utilization. Our findings reveal
that each alternative outperforms the existing options: RocksDB
excels in throughput and latency, Boltdb minimizes CPU usage,
and BadgerDB is most memory-efficient. This research not only
provides a roadmap for integrating new state databases into
Hyperledger Fabric but also offers critical insights for those
aiming to optimize enterprise blockchain systems. The study
underscores the significant gains in scalability and performance
that can be achieved by reconsidering the choice of state database.

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