Matterbeam

Old World Data Pipelines

Data pipelines are the plumbing of the modern enterprise — every analytics dashboard, AI model, and customer-facing product depends on data moving reliably from its source to destination. Despite being foundational infrastructure, traditional pipeline tools are inflexible, expensive, and difficult to scale. Every new use case requires building an entirely new pipeline from scratch which means weeks or months of engineering work. When something breaks or a schema changes, teams have to rebuild rather than replay. And as data volumes grow, the costs of tools like Fivetran or Hevo compound exponentially with pricing based on rows and connectors. The result is that data engineering teams are perpetually backlogged, AI projects stall waiting on data infrastructure, and companies are paying more and more for a system that's harder to manage.

Matterbeam: A Layer That Stores Data Streams and Feeds Every Destination

Matterbeam is a live data movement layer that fundamentally retools how data pipelines work. Rather than building one-way pipelines that only move data from point A to point B, Matterbeam stores the stream itself which creates a durable, replayable data log. From that single ingestion point, teams can transform data in transit, branch to unlimited destinations, replay historical data, and quickly develop new use cases. When schemas change or issues arise, teams can replay from the last known good point instead of rebuilding from scratch. The platform is serverless, priced on gigabytes of data moved rather than rows or connectors and typically delivers 50% to 80% cost savings compared to traditional tools. It also integrates with all the products that teams already use and requires no rip and replacement.

Why We Invested

We invested in Matterbeam because they have identified an architectural flaw in existing data pipelines and built a significantly better solution. The problem is large — every company with a data stack has it — and the cost and frustration of traditional tools is well understood by engineers and data leaders who use them daily. Matterbeam's stream-based architecture is a step change improvement; it changes the fundamental economics and flexibility of data movement that compounds in value as data grows. Early customers are seeing dramatic reductions in both cost and engineering overhead, and as AI workloads continue to demand more data, Matterbeam's platform is gaining more and more traction.

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