Feldera

It's time to build AI-era products that were impossible before.

Batch processing recalculates everything, even when 99.9% of your data didn’t change.

Feldera fixes that w/ incremental compute.

Bring your existing SQL and get millisecond freshness instead of hours-long (or days-long) batch jobs.

Can your incremental compute engine do this? **Feldera Incremental Computation Engine Benchmark Results** **Test Query Complexity:** - 61 input tables, 33 output views - 217 join operators (including left joins) - 27 aggregation operators - 287…

That’s actual incremental computation.

Read more: www.feldera.com/blog/can-you...

P.S. If your incremental engine can do this, we’d love to see the results.

We ran it on Feldera:
- 200ms update latency on input changes
- Single machine (16 CPU cores)
- 15GB RAM steady state

How?
Feldera does work proportional to your changes, not your table size. When you update one or many rows, we recompute only answers that changed and nothing else.

Query plan for a complex, real-world SQL program

This is a query plan for a real customer’s production SQL.
- 61 input tables -> 33 output views
- 217 joins
- 27 aggregations
- 218 projections and filters

Most systems would either do an expensive full recomputation or flat out fail.

Your pipeline was disrupted.

Feldera’s Health Page tells you why in seconds. No K8s access. No waiting on DevOps.

Details -> www.feldera.com/blog/introdu...

Introducing Feldera Health 🩺

A lightweight health monitoring solution built directly into Feldera. See the real-time status of your compiler, API server, and runner at a glance.

✅ Available today on try.feldera.com and Enterprise Feldera
📝 Detailed technical blog coming soon

January Edition 2026 The past many months have been busy for us at Feldera. We continue to ship compounding improvements for our customers when it comes to usability, performance and efficiency.

Incremental Updates - January 2026 edition is here! 🚀

This edition covers:
- Product updates: adaptive join rebalancing, GC for ASOF joins and more
- New blogs: deep dive into our profiler, constant folding in Calcite, and a look back at our progress in 2025

www.linkedin.com/pulse/januar...

🩻 X-ray vision for your SQL pipeline in Feldera.

-Click any node -> see metrics across all cores.
-Heat map shows bottlenecks instantly.
-Expand to trace back to your SQL code.

⚡ Seconds to see what used to take hours to find.

Dive deeper: www.feldera.com/blog/introdu...

Feldera in 2025: Building the Future of Incremental Compute Feldera's 2025 year in review: comprehensive SQL support, state-of-the-art infrastructure, advanced connectors, and the future of real-time analytics.

2025:
📦 166 unique releases, 1,162 changes, avg. new release every 2.4 days
📊 10x cost reduction for users, hours old insights into sub-second latency
⚡ 70-node Spark clusters -> single digit Feldera instances

2026: Make incremental compute inevitable

Full story: www.feldera.com/blog/feldera...

A visualization tool for the runtime behavior of Feldera pipelines We built a browser-based visualizer to dig into a Feldera pipeline's performance metrics. This tool can help users troubleshoot performance problems and diagnose bottlenecks.

Because when you're processing millions of changes per second, you need to see what's happening to optimize it.

Read the technical deep-dive: www.feldera.com/blog/introdu...

📊 Real-time metrics per operator: execution time, memory, data volumes, disk I/O
🎨 Visual dataflow graphs with color-coded performance heatmaps
🔍 Interactive exploration - click any operator to see detailed breakdowns

That’s why we built the Feldera profiler. It shows exactly where your computation time and resources are going.

You can’t optimize what you can’t profile.

Which operators are a bottleneck? Are there skewed joins? Why is storage use spiking?

Our engineering team used to spend hours trying to answer these questions when performance problems would show up in the wild.

They’re all available today. Now go build something fast. 🏎️

Backfill avoidance: modifying a query used to mean having to recompute & backfill all over again. With backfill avoidance, you can avoid another backfill by reusing existing states when applicable, & recomputing only what’s new. Much faster than starting over.

docs.feldera.com/pipelines/mo...

Fast backfill (HUGE steps): you know backfilling historical data can take forever. That's why we shipped a transaction API where you control the batch size - whether small or HUGE - for efficient bulk ingests.

docs.feldera.com/pipelines/tr...

Parallel compilation: we used to compile pipelines one at a time. Now we distribute the workload across multiple servers. Pipeline builds that were queued back-to-back can now complete simultaneously within minutes. It shaved an hour off of our CI pipeline!

docs.feldera.com/get-started/...

Rust Compilation can be slow. Backfills can take days. And no one likes to wait. ⏳

We’ve recently shipped features that will get you deploying faster and scaling more efficiently:

- Parallel Compilation
- Fast Backfill
- Backfill Avoidance

If you’re excited about hard technical problems and want to shape the future of real-time systems, Feldera is hiring (remotely!) for a Solutions Engineer (Enterprise) and a Software Engineer (Reliability, Performance)

jobs.ashbyhq.com/feldera/544a...

Hi Ben, I wanted to follow up on my recent note about your containerized solutions. If Feldera is exploring ways to improve mobility or streamline deployment, our container wheels could be a great fit. Here’s what our solutions offer: Increased flexibility Reduced operating costs Safe and practical mobility A more sustainable option With logistics hubs in both the US and EU, our casters are already helping teams in container rental, storage, and logistics cut down on equipment costs, labor, and time.

Some of my work at @feldera.bsky.social involves containers. I keep getting spam from some vendor who wants to sell me casters to put on the containers 🤣

How Feldera Customers Slash Cloud Spend (10x and beyond) By only needing compute resources proportional to the size of the change, instead of the size of the whole dataset, businesses can dramatically slash compute spend for their analytics.

"This is the true power of incremental compute. By only needing compute resources proportional to the size of the change, instead of the size of the whole dataset, businesses can dramatically slash compute spend for their analytics."

👇

www.feldera.com/blog/how-fel...

At @feldera.bsky.social I've been doing a lot of performance work. I needed an easy way to watch the Prometheus metrics for a pipeline, so I wrote a simple tool for the Feldera CLI that shows the pipeline metrics. Here's the progress of a pipeline that runs in about 30 seconds.

Stream Integration In this blog post we informally introduce one core streaming operation: integration. We show that integration is a simple, useful, and fundamental stream processing primitive, which is used not only…

If you've written even the most basic compute program, you've likely already written programs that "integrate".

Integration is central to Feldera and its underlying theory of incremental compute. It is also all around us in the real world! 👇

The future of data security isn't about choosing between compliance and performance. It's about making security a performance feature.

Learn how to implement fine-grained authorization without performance penalties: docs.feldera.com/use_cases/fi...

What if you could have both security AND speed?
Modern fine-grained authorization embeds security directly into data processing, delivering:

- Microsecond authorization decisions
- Real-time row/column-level filtering
- Automated compliance reporting
- Actually improved query performance

What are some the the typical challenges?
- 300-500ms latency added per query
- Complex compliance audits taking weeks
- Manual permission tracking via spreadsheets
- Performance degradation with granular controls

Traditional authorization systems force an impossible trade-off: secure data access OR fast query performance. With SOX compliance audits intensifying and data breach costs averaging $4.45M, this choice is becoming a business risk.

"We chose performance over security" - a dilemma no data team should face.

#DataEngineering #DataSecurity #RealTimeAnalytics

YouTube video by Feldera, Inc. How to Incrementally Get Results from Your Graph Data with Feldera

New tech talk:

How to Incrementally Get Results from Your Graph Data with Feldera.

Interested in practical techniques for incremental computation or want to see how this fits into modern data engineering workflows?

Check it out: youtu.be/vpVAZbaZ2Hg

Mihai Budiu, our exceptional Chief Scientist, won the 2025 #ACM #SIGCOMM Networking Systems Award for his groundbreaking work on #P4.

Details: www.sigcomm.org/awards/sigco...