Real-time
Data remains continuously current as business events occur, rather than being refreshed only through periodic batch processes.
An open industry initiative
A shared data architecture for the age of AI.
Streamhouse is an open, vendor-neutral category for data architectures that keep the current state of a business continuously available to production applications, analytics, and AI agents.
Definition
Streamhouse architectures empower organizations to capture, transport, transform, govern, and serve the current state of their business continuously, so that production applications and agents can act on it.
Change data capture, event streams, stream processing, open table formats, catalogs, and low-latency serving exemplify this approach.
Data remains continuously current as business events occur, rather than being refreshed only through periodic batch processes.
Engineered to production service levels, because business-critical applications, analytics, and agents depend on it continuously.
Meeting data where it already lives rather than requiring it to be consolidated first.
Organizations are beginning to deploy applications and AI agents that do more than analyze what happened in the past: they make decisions and take action as business events unfold.
To act reliably, these systems need fresh, governed business context delivered continuously and at production service levels.
The business context these applications and agents need is distributed across databases, applications, cloud services, and analytical systems.
The challenge is making that context available wherever it is needed, with the freshness, governance, and reliability that production use requires.
Architecture
Examples of this approach
Advancing an open category
“An open definition gives the industry shared language for this architecture and a common starting point for advancing the technologies and standards behind it.”
Streamhouse Working Group
Working Group
The Streamhouse Working Group is an open industry initiative founded by Aiven, Confluent, Redpanda, StreamNative and Ververica.
The group maintains a vendor-neutral definition of Streamhouse and works to advance the technologies, standards, and interoperability practices behind real-time, production-native, and decentralized data architectures.
Coined by Ververica, original creators of Apache Flink®.
Maintain and evolve the Streamhouse definition publicly through a versioned repository.
Advance the technologies, open standards, and interoperability practices needed to build Streamhouse architectures.
Encourage participation from customers, practitioners, technology providers, and the broader data community.
Preserve Streamhouse as an open, vendor-neutral category that no single company controls.
Streamhouse architectures empower organizations to capture, transport, transform, govern, and serve the current state of their business continuously, so that production applications and agents can act on it. Read the complete definition.
No. Streamhouse is a vendor-neutral architectural category. Organizations can build one with open-source technologies, commercial products, or both.
The Streamhouse Working Group maintains an open, vendor-neutral definition of the category, grounded in the open source projects and open standards on which these architectures are built.
Anyone may use Streamhouse to describe, discuss, implement, market, or analyze architectures consistent with the open definition without permission, notice, registration, or fees. Read the Trademark Commitment
Aiven, Confluent, Redpanda, StreamNative and Ververica established the Streamhouse Working Group and published an open, vendor-neutral definition of Streamhouse.
The canonical Streamhouse definition will be maintained publicly through a versioned GitHub repository.