Artie has closed a Seed round of $3.3M to make database replication real-time, reliable, and cost-effective.
Exponent Founders Capital led the round with participation from General Catalyst, Y Combinator, and angel investors including Benn Stancil, Lenny Rachitsky, and Arash Ferdowsi.
Artie is unique in its use of change data capture (CDC) and streaming technology to sync data, along with the ability to automatically handle schema evolution in-flight.
Today, the majority of companies are still utilizing batched ETL (extract, transform, load) processes to sync data. This introduces data lag in the data warehouse, hindering real-time analytics and operational use cases, and results in data consistency and scalability issues.
Artie’s software ensures high data integrity while dramatically reducing latency to seconds. It also saves money by eliminating the need to process large batches of data. Customers are then able to operationalize their data warehouse and generate more timely, impactful insights.
For example, Substack, a leading subscription network, previously used batched ETLs to move production data from its databases into Snowflake. 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, which lowered overall organizational productivity. After implementing Artie, data lag was slashed dramatically to a mere 10-15 seconds. Substack’s A/B testing framework now measures much faster and data integrity also improved. The result is a tangible acceleration in decision-making processes across the entire company.
“One common misconception about real-time streaming is its presumed higher cost compared to batch processing,” says co-founder and CEO Jacqueline Cheong. “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.”
Companies with large volumes of data stand to benefit the most, explains co-founder and CTO Robin Tang, who previously scaled infrastructure at Opendoor, Zendesk, and several early-stage startups. “While not immediately intuitive,” he says, “processing smaller amounts of data continuously using Snowflake’s virtual data warehouse requires less computational power than ingesting bulk data every 1-2 hours.”
Who benefits from real-time data? A wide range of industries. Fintech companies, for instance, rely on it for risk analysis and transaction monitoring. Ecommerce companies use real-time data to monitor inventory levels, optimize warehouse logistics, and iterate on experiments. For advertising 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 access to the latest production data. The importance of real-time data escalates even more when companies provide analytical dashboards to their customers. While internal BI 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 has achieved remarkable growth. Having launched six months ago, it has 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 in the past few months. With the infusion of new funding, it plans to expand the team to support its pipeline of high-growth and innovative companies. To experience how real-time data can elevate your competitive edge, contact us to discuss your use case.
For more such updates, follow us on Google News Martech News