Traditional pipeline tools just move rows and send you the bill. Matterbeam stores the stream, transforms in transit, and branches to every destination you need.
Cut movement costs up to 80% while gaining replayability, backfills, and fine-grained control without re-hitting your source systems.
When data flows through Matterbeam, it becomes durable, explorable, and reusable.
These capabilities come with the platform, not asa pile of add-on tools.
Built on cloud primitives so you get elastic scale and economical operation, not fixed capacity overhead.
+ Scale up for spikes, scale downwhen idle
+ We’re not just reselling EC2, Matterbeam is truly serverless
No record math. No “active vs inactive” surprises. Matterbeam charges on GB of data movement.
+ Simple, transparent pricing
+ Aligned with the work actually done
Pipelines break when the real world changes. Matterbeam is designed to be self-healing and resilient.
+ Less babysitting and firefighting
+ Recover and move forward without rebuilds
Streaming-native transforms help keep data fresh and avoid “stale between batches” behavior.
+ Transforms in motion
+ Real-time and batch in one model
When data flows through Matterbeam, it becomes durable, explorable, and reusable. These capabilities come with the platform, not as a pile of add-on tools.
Don’t just take our word for it.
If it holds data, Matterbeam can connect, shape, and emit it anywhere.
Traditional migrations drag on because you cannot test without disrupting production. With Matterbeam, try, retry, and perfect each step before cutover. All from the same interface you use for AI workloads.
Keep legacy and target in sync while you test. Diff results, fix issues, and switch when ready.
Cut over by dataset or workload. Verify parity before switching consumers. Roll back instantly if needed.
Replay from any point in history. Recover from errors, audit every record, and inspect transforms.
Collectors pull from any system. Emitters shape JSON, Parquet, vectors, or tables for any target.
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Traditional pipelines are brittle, one-directional, and purpose-built. If you need data for a new report, AI model, or dashboard, you’re starting from scratch. Each pipeline is a separate engineering project.
Matterbeam flips this. Your data flows into immutable datasets once. From there, you can:
- Add new transforms or emitters without touching the source
- Replay historical data through new logic
- Time travel to any point in your data history
- Spin up new use cases in minutes, not months
Matterbeam is more than a connector-based pipeline tool. While traditional tools like Fivetran focus on copying data and charging based on rows and connectors, Matterbeam is a live data movement layer that stores the stream once, supports in-transit transforms, and enables replayability without re-reading production systems.
That architectural difference reduces pipeline rebuilds, eliminates record-based pricing surprises, and gives teams far more control over how data flows. As a result, customers typically see 50–70% lower data movement costs compared to Fivetran, especially as their stack and data volumes grow.
Hevo is designed as a no-code ELT pipeline tool focused on extracting and loading data into warehouses. Matterbeam is built differently. It’s a live data movement layer that stores the stream once, supports transforms during transit, and enables replayability without re-reading production systems.
Instead of managing connector jobs and record-based pricing, teams move data through a durable stream architecture with transparent, GB-based pricing.
That architectural shift reduces rebuilds, increases control, and typically results in 50–70% lower data movement costs compared to traditional pipeline tools as data volume and destinations scale.
Absolutely. This is where we shine.
Most AI projects fail because teams can’t access the data they need when they need it. Getting historical data cleaned and prepared takes months. By the time data is ready, the project timeline is blown.
With Matterbeam:
- Data scientists access datasets directly
- Time travel gives instant historical data for training
- Transforms let them experiment with features fast
- No waiting for data engineering sprints
One customer went from 6-month data projects to 2-week delivery using Matterbeam. The AI team ships models, not tickets.
AI/ML projects blocked by data access: Give data scientists instant access to clean historical data. Time travel to create training sets in hours instead of months. 95% of AI projects fail on data infrastructure, not models.
Data migrations and integrations: Collect from old and new systems into unified datasets. Replay historical data as you migrate. No temporary pipelines to throw away later.
Engineering backlogs measured in quarters: Every use case needs a new pipeline, so simple requests take months. Matterbeam collects once, use anywhere. Deliver in days.
Customer 360 views: Combine Salesforce, Stripe, support tickets, and product usage. Updates stream in real-time as data changes across systems.
Real-time analytics without infrastructure burden: Stream from production databases to warehouses without impacting performance. Keep dashboards fresh without batch delays or brittle pipelines.
No, you don't need to replace anything. Matterbeam works alongside everything you have today – your data warehouse, BI tools, databases, and existing pipeline tools like Fivetran, Hevo, or Airbyte.
But once teams experience replay and transformation capabilities (replay historical data, transform on the fly, test without breaking production), they naturally phase out their point-to-point tools. These are capabilities traditional tools simply can't match.
Plus, Matterbeam is cheaper. Instead of paying for three Salesforce connectors to send data to three destinations, you pay for one collector and spin up unlimited emitters. No triple billing. Teams typically save 50-70% while gaining capabilities they never had before.
Start with Matterbeam alongside your current stack. Let the replay functionality and cost savings speak for themselves.
Contact us to discuss your needs. We work with design partners on custom arrangements that let you prove value before committing.
