Artie announced it had closed a seed round of $3.3 million to make database replication real-time, reliable, and cost-effective. Exponent Founders Capital led the funding round with participation from General Catalyst, Y Combinator, and angel investors, including Benn Stancil, Lenny Rachitsky, and Arash Ferdowsi.
Artie is unique for its use of change data capture (CDC) and streaming technology to sync data along with the ability to handle schema evolution in-flight automatically. And the majority of companies are still utilizing batched ETL (extract, transform, load) processes to sync data. This introduces data lag in the data warehouse, which hinders real-time analytics and operational use cases and results in data consistency and scalability issues.
Artie’s software drives high data integrity while dramatically reducing latency to seconds. And it also saves money by eliminating the need to process large batches of data. Then, customers can operationalize their data warehouse and generate more timely, impactful insights.
For example, Substack previously used batched ETLs to move production data from its databases into Snowflake. And these batches would transfer data every few hours or even overnight. This delayed its data analysts’ ability to analyze experiment data and initiate new workflows, lowering overall organizational productivity. After implementing Artie, data lag was slashed dramatically to just 10-15 seconds. Substack’s A/B testing framework now measures much faster and data integrity was also improved.
A wide range of industries benefit from real-time data. For example, fintech companies rely on it for risk analysis and transaction monitoring. And e-commerce companies use real-time data to monitor inventory levels, optimize warehouse logistics, and iterate on experiments. For ad agencies, the use of real-time marketing analytics enhances campaign effectiveness and the ability to personalize outreach.
Companies employing AI models for incremental or online machine learning depend on the access to the latest production data. And the importance of real-time data escalates even more when companies provide analytical dashboards to their customers. While internal business intelligence teams might manage with some data delay, expecting customers to endure even brief lags in data is increasingly seen as unacceptable in today’s fast-paced environment.
Artie achieved remarkable growth. Having launched six months ago, it scaled from processing zero to over 30 billion rows of data. It is now serving over 10 enterprise customers and has experienced significant revenue growth of mid-double digits month-over-month over the past few months. With the new funding round, the company plans to expand the team to support its pipeline of high-growth and innovative companies.
KEY QUOTES:
“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.”
- Artie co-founder and CEO Jacqueline Cheong
“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.”
- Artie co-founder and CTO Robin Tang, who previously scaled infrastructure at Opendoor, Zendesk, and several early-stage startups
