Artie, a pioneering tech firm specialising in real-time database replication, has successfully closed a Seed funding round, securing $3.3m in investment.
The funding was led by Exponent Founders Capital, with significant participation from venture capital heavyweights General Catalyst and Y Combinator, alongside notable angel investors including Benn Stancil, Lenny Rachitsky, and Arash Ferdowsi.
The tranche will fuel Artie’s mission to further develop its cutting-edge technology and expand its market reach. The company aims to enhance its product offerings and accelerate customer acquisition efforts, targeting enterprises seeking to optimise their data infrastructure for real-time applications.
The London-based startup is revolutionising the realm of database replication by offering a solution that ensures real-time, reliable, and cost-effective synchronisation of data.
Unlike conventional methods that rely on batched ETL processes, Artie utilises change data capture (CDC) and streaming technology to synchronise data instantaneously. Additionally, it automatically handles schema evolution in-flight, eliminating the complexities associated with traditional data replication methods.
The groundbreaking software addresses the prevalent challenges faced by companies utilising batched ETL processes, such as data lag, consistency issues, and scalability constraints. By significantly reducing latency to mere seconds and ensuring high data integrity, Artie empowers organisations to leverage real-time analytics and operational insights effectively.
Co-founder and CEO Jacqueline Cheong, said, “One common misconception about real-time streaming is its presumed higher cost compared to batch processing. Artie’s customers tell a different story: not only do they benefit from real-time data, but they often also see a reduction in total cost of ownership.”
Co-founder and CTO Robin Tang, who previously scaled infrastructure at Opendoor, Zendesk, and several early-stage startups, added, “Companies with large volumes of data stand to benefit the most. While not immediately intuitive. Processing smaller amounts of data continuously using Snowflake’s virtual data warehouse requires less computational power than ingesting bulk data every 1-2 hours.”
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