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Ververica

Announcing The Private Preview Program For Apache Fluss™ On Ververica Platform

Jaime López
Jaime López

Director of Product Excellence

Vladimir Jandreski
6 min read

The Lakehouse Was Built For Yesterday. Fluss Is Built For Tomorrow.

For a decade, streaming compute has moved faster than streaming storage. Apache Flink® unifies batch and streaming at the compute layer, and most teams settle the storage question by gluing systems together. It works but it means the same data lives in three or four places, and both the bill and the complexity grow underneath.

That old pattern has run its course. Today we are announcing a Private Preview for Apache Fluss on Ververica Platform, working with a small group of customers to build the missing piece that will take business-critical and AI use cases to the next level.

Figure 1: Apache Fluss on Ververica Platform: Announcing the Fluss Private Preview

What Fluss Does And How It Completes The Streamhouse™ Vision

Fluss is a streaming storage layer for real-time analytics. The idea is straightforward: a single layer that unifies streaming and batch, serving real-time and historical data in a single, fully-queryable copy of data.

Fluss makes the live stream itself queryable, like a table. You write an event once, and that single copy serves your applications, analytics, and AI models at the same time, fresh within a second. Recent data stays fast in Fluss. Older data tiers automatically to low-cost lakehouse storage, and a single query reads across both using union reads. No duplicate pipelines to reconcile. No replay tax. No gap between what happened and what you know.

Figure 2: Apache Fluss unifies batch and streaming

Fluss is the storage foundation of the Streamhouse™, our architecture where one copy of data serves every workload. Streamhouse is Ververica's architecture for bridging the lakehouse and streaming worlds, so real-time and historical data stop living as separate systems. We have written before about why batch lakehouses fall short and how Streamhouse closes that gap.

It is built around a single guiding principle: one copy of data, serving every workload. These workloads include streaming ingestion, low-latency operational analytics, batch processing, machine learning features, and AI context; all without incurring a multiple systems tax that conventional architectures accumulate. Streamhouse combines an open-source streaming storage layer (Apache Fluss), an open lakehouse tier (like Apache Paimon™ or Apache Iceberg®), a unified batch-and-stream processing engine (VERA, 100% compatible with Apache Flink®), declarative data pipelines (Materialized Tables), a freshness-aware workflow scheduler, and an autoscaling service (Autopilot) into a single operational substrate. We covered the architecture in full when we brought Fluss to Ververica Platform, and the Private Preview is how we turn it into a production-grade product.

Figure 3: The Ververica Streamhouse Architecture

Why It Matters

The most immediate use case Fluss solves are the high-performance workloads enterprises already run. Fraud scoring, recommendation engines, live pricing, and real-time risk can run off one governed table instead of a stack of reconciled systems. Stateful jobs stop dragging terabytes through every checkpoint. Batch and streaming pipelines collapse into a single definition, so the two stop disagreeing and nobody spends the morning working out which number to report to the regulator.

But where we think Fluss will have the biggest impact is in AI use cases. AI silently degrades when training data and serving data live in separate systems and drift apart. Experts call this training-serving skew. Fluss addresses this by providing a unified source for both real-time signals and historical context. Computing features once and serving them for both offline training and online inference from the same table, agents read current, authoritative context instead of stale snapshots, so they reason against what is true now, not yesterday’s news. We foresee this being especially impactful in banking, healthcare, manufacturing and insurance.

Real-time AI does not work without real-time storage that is governed, fresh, and reproducible. That is the building block Fluss provides, and why Ververica is placing it as the center of what comes next.

The Fluss Private Preview

The Fluss Private Preview is a framework to build a market-ready product hand-in-hand with users tackling today’s real-world problems. We are bringing managed Apache Fluss to Ververica's Unified Streaming Data Platform, and we are shaping what it becomes with the people who run it. Ververica offers enterprise robustness and world-class Fluss know-how, working directly with each program participant so their real needs decide how the GA product is built.

Figure 4: Apache Fluss Private Preview

We are running it with a small, hand-selected group of companies whose workloads sit where Fluss makes the biggest difference. Several enterprises approached Ververica early on, describing the exact problems Fluss solves, and reinforcing that Ververica is reading the market needs correctly. These same enterprises will gain an early mover advantage as part of the Fluss Private Preview, directly influencing what ships at GA.

Streaming compute had its breakthrough years ago. Storage just caught up to it. A handful of companies are building with us what comes next, and in the near future it will be available for all.

While the world buffers, we act.

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