Artie Raises $12M Series A to Stream Real-Time Database Feeds
Most data engineering teams still sync operational databases to data warehouses using batch pipelines scheduled every few hours or days. When companies attempt to build sub-minute streaming pipelines in-house, the builds often consume engineering teams for a year or more without reaching production stability. Artie sells managed software that automates the entire process, moving data from production databases like PostgreSQL directly to analytical platforms like Snowflake using change data capture (CDC).
Following a $12 million Series A round reported by Axios and led by Standard Capital, the San Francisco startup is expanding its 12-person team. In an interview on YC Root Access, the founders disclosed that Artie processed over 700 billion rows of data over the previous 12 months—a 12-fold increase over the prior year—and plans to triple its headcount across engineering and sales.
Replacing In-House CDC Pipelines
Artie was founded by Jacqueline Cheong and Robin Tang, who went through Y Combinator's Summer 2023 batch. Tang previously worked as a staff software engineer at Zendesk and Opendoor, where he repeatedly ran into the limits of scheduled ETL setups.
At Zendesk, Tang worked with Maxwell, an open-source tool reading MySQL binlogs into Apache Kafka. Later at Opendoor, he spent a year working with a seven-person engineering team trying to build an in-house pipeline pairing Debezium, Confluent, Kafka, and custom merge scripts. As Tang explained in a conversation with Standard Capital's Dalton Caldwell, the project never reached production reliability. Seeing that high-growth businesses like Netflix, DoorDash, and Instacart had to build massive custom distributed platforms to handle change data capture reliably, Tang and Cheong set out to package that infrastructure into a turnkey product.
Cheong, who previously worked as an investment analyst at Balyasny Asset Management and an associate at Bank of America Merrill Lynch, validated the problem across engineering leaders before the pair left their roles to build the product. Artie landed its first customer, Substack, by sending a cold email to its head of data. Substack ran a proof-of-concept testing billions of rows from its production PostgreSQL database to Snowflake before going live.
Today, Artie guarantees sub-minute data synchronization while avoiding heavy queries against live production databases. Rather than querying tables by timestamps, Artie attaches directly to the database transaction log. Its backends and open-sourced engine, Artie Transfer, are written in Go, running on Kubernetes with Helm and Terraform, and processing streaming change events through Apache Kafka. Its customer-facing dashboards are built using React, TypeScript, and Material UI, while marketing systems use Next.js and Tailwind CSS.
The Shift to Operational and AI Workloads
Data freshness requirements have tightened as companies shift data warehouses from backward-looking business intelligence reporting into live operational systems. In an interview on the New York Stock Exchange floor, Cheong pointed out that fintech companies rely on real-time database synchronization to catch fraud instantly, while e-commerce platforms use it to balance inventory against immediate demand.
More recently, generative AI models and autonomous agents have added pressure. Because downstream customer support bots and automated agents interact directly with end users, running them on batch data that is hours old leads to hallucinations or contradictory actions. Cheong noted in the Standard Capital interview that over 50 percent of the company's incoming pipeline now stems from teams building AI-driven workflows that demand fresh, consistent production data.
Artie handles the operational edge cases that usually derail in-house implementations, such as online backfilling using methods modeled after Netflix's DBLog, handling out-of-order writes during Kafka rebalancing, and merging tens of thousands of partitioned or sharded tenant tables into unified analytical views.
Hiring In-Person in San Francisco
Artie runs as an in-person team working five days a week out of an office in San Francisco's Financial District. The company crossed $1 million in annual recurring revenue with just four people—the two founders and two software engineers—and is now filling core technical and commercial roles.
On the engineering side, the team is hiring a Senior Software Engineer to work on distributed systems, native CDC connectors, schema change alerts, column encryption, and analytics portals. The company is also adding a Product Engineer to interact directly with technical customers and build features such as column exclusion, encryption, and alert systems.
To build out its commercial operations, Artie is hiring a Senior Business Development Representative - Enterprise to lead outbound prospecting into data engineering teams and AI startups. High-touch enterprise deals are supported by a Solutions Engineer, who runs structured proof-of-value technical engagements and assesses customer data architectures alongside the founders, and an Enterprise Account Executive tasked with sourcing and closing enterprise deals end-to-end.
Open Positions at Artie
| Role | Location | Work Mode | Salary |
|---|---|---|---|
| Senior Software Engineer | San Francisco, CA, US | Onsite | $150,000 – $250,000 |
| Product Engineer | San Francisco | Onsite | $150,000 – $250,000 |
| Solutions Engineer | San Francisco, CA, US | Onsite | $175,000 – $200,000 |
| Enterprise Account Executive | San Francisco, CA, US | Onsite | $240,000 – $320,000 |
| Senior Business Development Representative - Enterprise | San Francisco, CA, US | Onsite | $115,000 – $150,000 |
