Since introducing DeltaStream, our mission has been to build a comprehensive stream processing platform that is easy to use and easy to operate. I’m excited to introduce DeltaStream Fusion—a Unified Analytics Platform— bringing together streaming, real-time, and batch analytics into a single integrated solution. DeltaStream Fusion enables users to build high performance streaming pipelines, create real-time materialized views directly from streaming data and perform complex batch analytics on lakehouse data—all within one platform. 

With these capabilities, organizations can seamlessly handle diverse workloads, from real-time data ingestion for training applications and IoT analytics, to real-time dashboards and sophisticated batch analyses, without having to manually stitch together different platforms and creating silos.

Why We Built DeltaStream Fusion

DeltaStream began as a managed, serverless platform built around Apache Flink to process, govern and share streaming data. Typically, data is ingested into streaming storage systems and made available to downstream consumers, including data lakehouses—a common destination for streaming data. Often, data moves through multiple specialized systems: streamed data is processed by streaming platforms, stored in lakehouses, then queried by separate batch analytics engines. 

Consider the common example of clickstream analytics: weblog pageview events are enriched and aggregated via a streaming pipeline, then stored and analyzed separately within a lakehouse.

We see similar patterns of fragmentation in real-time analytics, where streaming data is stored in a real-time analytics database to power live dashboards or user-facing analytics.

A fragmented analytics landscape creates many inefficiencies. Managing separate analytics stacks for streaming, batch, and real-time workloads leads to: 

  • Operational complexity, where each tool requires specialized knowledge, unique deployment methods, and dedicated infrastructure.
  • Redundant infrastructure costs, as organizations deploy multiple tools that often overlap in functionality.
  • Data duplication and synchronization issues, especially when trying to maintain consistency across disparate systems.
  • Governance and compliance challenges, as teams must enforce security and policy standards in multiple places, increasing the risk of errors or non-compliance.

A unified analytics platform capable of supporting all analytics workloads would address these challenges. This is the main motivation behind DeltaStream’s Fusion platform.

The Unified Analytics Advantage

DeltaStream Fusion brings real-time, batch, and interactive analytics together in one seamless platform—so users can go from raw data to insights without jumping between tools.

With Fusion, teams can:

  • Build real-time streaming pipelines to prep data on the fly
  • Write that data to a lakehouse for long-term storage and deeper analysis
  • Instantly query and process both streaming and batch data—all within the same platform

Fusion also makes it easy to create real-time materialized views from streaming data, so you can deliver up-to-the-second insights to dashboards, applications, or end users—without ever leaving DeltaStream.

This unified architecture simplifies even the most complex analytics workflows. There's no need to stitch together multiple systems or manage infrastructure. As a cloud-native, serverless solution, Fusion automatically chooses the best engine for the job:

  • Apache Flink for streaming
  • Apache Spark for batch
  • ClickHouse for low-latency queries

The diagram above shows how clickstream analytics flows through Fusion: streaming and lakehouse data are connected, processed, and queried—all in one place. Thanks to built-in real-time analytics capabilities, Fusion can deliver sub-second latency insights to power rich, responsive user experiences.

What You Can Do with DeltaStream Fusion

DeltaStream Fusion unlocks powerful analytics use cases across industries in one unified platform, without the complexity of managing separate tools or stitching together workflows.

Organizations can now build:

  • Real-time fraud detection systems that adapt as threats emerge
  • Predictive maintenance pipelines for IoT fleets based on live telemetry
  • Customer 360° analytics to personalize experiences with up-to-the-second insights
  • Financial analytics that blend real-time risk scoring with deep historical trend analysis

Moreover, businesses can deploy interactive dashboards powered by real-time materialized views, enabling instant insights for operational decisions. By integrating streaming, batch, and real-time querying together in one cohesive platform, DeltaStream Fusion gives data teams the agility to iterate faster, uncover deeper insights, and move from raw data to action in record time.

A Shift-Left in Analytics

Fusion also enables a critical shift in how organizations approach analytics—away from traditional batch-oriented platforms like Snowflake, Databricks, and Redshift, and toward continuous streaming as the default mode to process data. 

This shift brings major advantages:

  • Lower infrastructure and compute costs
  • Faster access to insights, reducing time-to-decision
  • Fewer data pipelines and systems to manage, cutting operational overhead

With native support for Apache Iceberg and seamless integration with platforms like Snowflake and Databricks, Fusion lets you unify batch and streaming into a single, governed pipeline—reducing duplication, maintaining consistency, and improving overall cloud efficiency.

Join the Early Access Program

We’re thrilled to open early access to DeltaStream Fusion, our next-generation Unified Analytics Platform. By breaking down silos and eliminating the complexity of hybrid stacks, Fusion enables organizations to build more agile, real-time data systems that drive innovation and competitive edge.

Spots are limited—sign up now to reserve your place and unlock the next generation of analytics.