Unlocking the Power of Raft Consensus with rqlite using Python
07-20, 10:30–11:00 (Europe/Prague), North Hall

Distributed databases are widely used in modern applications for their high availability and scalability. Have you ever wondered how data integrity is maintained with the data across multiple nodes? One of the key components of achieving this is distributed consensus. Raft is a widely used consensus algorithm that provides a fault-tolerant and highly available system. In this talk, we will explore how to implement Raft consensus using the rqlite distributed database in python.

Consensus is a fundamental problem in distributed systems, and it is critical for maintaining data consistency and availability in applications. In this talk, we will explore how to implement Raft consensus using rqlite, a distributed database that uses SQLite as its storage engine.

We will begin with an overview of distributed databases and the need for consensus algorithms, followed by a deep dive into the key concepts of the Raft consensus algorithm. We will discuss how Raft ensures consistency and availability in a distributed system and explore its strengths and weaknesses compared to other consensus algorithms.

We will then focus on rqlite, a powerful tool for building distributed databases with Raft consensus. We will cover its key features, including its SQL interface, fault tolerance, and scalability. We will also demonstrate how to use rqlite in Python applications to build fault-tolerant and highly available distributed systems.

Attendees will gain a deeper understanding of the key concepts of distributed consensus, the benefits of using the Raft algorithm, and how to implement it using rqlite in python. No prior knowledge of consensus algorithms, Raft, and rqlite is required, but some familiarity with databases would be helpful. This talk is suitable for developers, database enthusiasts, and anyone interested in distributed systems and database design.

Expected audience expertise


Tanya Sneh is a passionate software engineer and an alumnus of IIT Kharagpur, India. She has previously worked on projects involving game theory, machine learning, and robotics. Currently, she is focused on building scalable applications and working with multiple database technologies in the fintech industry. In addition to her professional pursuits, Tanya is a strong advocate for women in technology and has mentored several women in this field. She is known for her dedication to community involvement and enjoys reading and painting in her leisure time.