Streamhouse-ready

Build a Streamhouse on WarpStream

WarpStream is a Streamhouse-ready platform. It covers every capability in the Streamhouse definition (capture, transport, transform, govern, and serve), and it all runs in your own cloud account, on your own object storage.

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Streamhouse Definition

What is a Streamhouse?

A Streamhouse is an open, vendor-neutral architecture for keeping the current state of a business continuously available. Production applications, analytics, and AI agents can then act on that data as events happen, not hours later.

The Streamhouse Working Group defines it by five capabilities (capture, transport, transform, govern, and serve) and three attributes: real-time, production-native, and decentralized. The term was coined by Ververica, and the definition was approved on September 15, 2026. Read the full definition

Is WarpStream a Streamhouse?

A Streamhouse is an architecture, not a single product. WarpStream is a Streamhouse-ready product built for Streamhouse architectures. It provides Kafka-compatible event streaming, Iceberg tables, stream pipelines, and governance, with every component deployed in your own cloud.

What is a Streamhouse?
Every Capability, One Platform
The Three Attributes
Reference Architecture
Why AI Agents Need a Streamhouse
Customers
FAQs

Every Streamhouse Capability, One Platform

Here's how WarpStream maps to each capability in the Streamhouse definition.
01
Capture
App producers + CDC via Managed Data Pipelines
02
Transport
Kafka-compatible BYOC on object storage
03
Transform
Managed Data Pipelines
04
Govern
Schema Registry, Validation, Schema Linking
05
Serve
Live Kafka consumers + Tableflow Iceberg tables
Capability
What It Means
How WarpStream Delivers It
Capture
What it means
Pull business events and database changes as they happen.
WarpStream
Application producers send events with standard Kafka clients. Change data capture from sources like Postgres through Managed Data Pipelines.
Transport
What it means
Move events reliably between systems.
WarpStream
Apache Kafka–compatible streaming built directly on object storage, with no local disks to manage.
Transform
What it means
Shape, filter, and enrich data in motion.
WarpStream
Managed Data Pipelines for in-stream transformation, configured in YAML and run inside the Agents.
Govern
What it means
Keep data consistent, trustworthy, and controlled.
WarpStream
Data Governance via Schema Registry, Schema Validation, and Schema Linking, plus Kafka ACLs, ACL Shadowing, and Audit Logs.
Serve
What it means
Make current data usable by apps, analytics, and agents.
WarpStream
Kafka consumers read streams directly. Tableflow materializes topics as Apache Iceberg tables for Snowflake, Databricks Unity Catalog, BigQuery, AWS Glue, and engines like DuckDB and ClickHouse.
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Real-Time. Production-Native. Decentralized.

Real-Time
Data stays continuously current as events happen, with no batch refresh windows. WarpStream streams every event as it's produced, and Tableflow keeps Iceberg tables incrementally up to date.
Production-Native
Stateless Agents scale automatically, and durability comes from object storage, so there are no brokers to babysit, disks to rebalance, or partitions to reassign.
Decentralized
With BYOC, compute and storage run in your VPC, and raw data never leaves your environment. Tableflow also ingests from any Kafka-compatible source, so there's nothing to consolidate first.

A Streamhouse on WarpStream, End to End

Changes flow from operational databases and applications into WarpStream through CDC and Managed Data Pipelines. WarpStream transports and governs them as Kafka-compatible streams. Tableflow materializes them into Iceberg tables your query engines and catalogs already understand, while applications and AI agents consume the same data live from the stream.
Sources
Postgres
and other databases
Apps and services
Kafka producers
Your cloud account (WarpStream BYOC)
Managed Data Pipelines
01 Capture (CDC) and 03 Transform: filter, enrich, route
Stateless Agents + your object storage bucket
02 Transport: Kafka-compatible topics
Schema Registry
04 Govern: Validation, Linking
Tableflow
05 Serve: Iceberg tables
Raw data never leaves your account
Serve
Apps and AI agents
live Kafka consumers
Sinks
ClickHouse and others
Query engines
Snowflake, Databricks, BigQuery

Every Streamhouse capability runs inside your own cloud account. Consumers read live streams, and query engines read Iceberg tables from the same data.

Why AI Agents Need a Streamhouse

Agents don't just report on what happened. They make decisions and take actions, which requires fresh, governed business context delivered continuously, not a nightly snapshot.

WarpStream gives agents the same live, schema-validated data your production applications use, while your analytics team queries it as Iceberg tables.

Start with the data you already stream
Tableflow can build Iceberg tables from any Kafka-compatible cluster, including open-source Kafka, Amazon MSK, and Confluent Cloud.
Learn About Tableflow

Streamhouse Foundations, Already in Production

Read the Case Study
5 GiB/s pipeline
Prompts stream into WarpStream, and Managed Data Pipelines feed real-time trust and safety classifiers, A/B testing, the data warehouse, and a feature store, all inside their own cloud.
“WarpStream is the most boring product I've ever got to work with. In infra, that's the biggest compliment you can ever give someone. It just works.”
Maor Bril, Character.AI

Explore WarpStream

Bring Your Own Cloud
WarpStream's hybrid BYOC deployment model provides the ease of use of a fully cloud hosted solution, but the cost profile, security, and data sovereignty of a self-hosted deployment.
Data Governance
Store all your schemas in WarpStream's Confluent-Compatible BYOC Schema Registry. Do stateless, quick deploys and manage traffic spikes with auto-scaling.
Orbit
Orbit allows you to automatically replicate topics (including record offsets), consumer groups, offset gaps, ACLs, and cluster configurations.
Multi-Region Clusters
Multi-Region Clusters guarantee  zero data loss (RPO=0) out of the box with zero additional operational overhead. Multi-region consensus and automatic failover handling.
Managed Data Pipelines
ETL and stream processing from within your WarpStream Agents and cloud account. No additional infrastructure needed. You own the data pipeline – end to end.
Integrations
WarpStream supports sending data to and from 100+ different sources and destinations out of the box. Just pick your integration and plug it in seamlessly.
WarpStream Tableflow
New!
Tableflow is an Iceberg-native database that materializes tables from any Kafka topic and automates ingestion, compaction, and maintenance. A truly complete real-time data lake solution.
Tableflow data lake architecture diagram
Why Switch?
Learn why teams are switching to WarpStream and choosing a simpler, faster, cloud-native way to stream data at a fraction of the cost.
WarpStream Lightning Topics: 33ms on S3. The trade-off is over.
Learn More

FAQs

Don't see an answer to your question? Check our docs, or contact us directly.

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What is a Streamhouse?

A Streamhouse is an open, vendor-neutral data architecture that keeps a business's current state continuously available to production applications, analytics, and AI agents. It's defined by five capabilities (capture, transport, transform, govern, and serve) and three attributes: real-time, production-native, and decentralized.

Who defines the Streamhouse category?

The Streamhouse Working Group maintains the definition. Its founding members are Aiven, Confluent, Redpanda, StreamNative, and Ververica. The term was coined by Ververica, which administers the Streamhouse trademark on behalf of the Working Group.

Can WarpStream be used to build a Streamhouse?

Yes. WarpStream is a Streamhouse-ready product that covers all five capabilities. CDC and Managed Data Pipelines handle capture and transformation. Kafka-compatible streaming on object storage handles transport. Data Governance is provided via Schema Registry, Schema Validation, and Schema Linking, plus Kafka ACLs, ACL Shadowing, and Audit Logs. Kafka consumers and Tableflow's Iceberg tables handle serving.

How is a Streamhouse different from a lakehouse?

A lakehouse centers on analytical data at rest. A Streamhouse keeps data continuously current and makes it usable by production systems and agents, not just analysts. Open table formats like Iceberg, which Tableflow produces, are one piece of a Streamhouse.

Do I need to migrate off my existing Kafka to use Tableflow?

No. Tableflow can ingest from any Kafka-compatible cluster, including open-source Kafka, Amazon MSK, and Confluent Cloud.

Does my data leave my cloud account?

No. In WarpStream's BYOC model, raw data is processed on your VMs and stored in your own object storage buckets.

Is WarpStream a member of the Streamhouse Working Group?

WarpStream is part of Confluent, a founding member of the Streamhouse Working Group.

Streamhouse is a trademark administered by Ververica on behalf of the Streamhouse Working Group. The definition is maintained at streamhouse.com and on GitHub.