Unite past + present data for a next-level advantage
Apache Kafka holds your most recent truth. Apache Iceberg holds your history.
Streambased delivers a unified view of real-time and historical data by making Kafka and Iceberg queryable together - without copying data, building new pipelines or changing the tools your teams rely on.
By removing the boundary between Kafka and Iceberg, the distinction between real-time and historical systems disappears, unlocking use cases that radically expand what's possible with your data.
- Zero Copy
- Zero drag
- Total data
- Total control
Unified view
Watch it sweep across time - or drag it yourself
Streaming straight from Kafka - no delay, no pipeline.
Live
+ historical
1
unified table
0
data duplicated
Work your data across time, without boundaries
Query Kafka and Iceberg as one
Simplify streaming and analytics architecture
Reduce storage duplication from ingestion pipelines
Power AI with fresher behavioural data
Detect signals with historical context
Reason across time, not systems
Zero-copy
Real-time Iceberg Without Pipelines
Stop waiting on batches. With its unique zero-copy approach, Streambased turns your real-time Kafka data into your single Iceberg unified view in milliseconds, not hours.
Purpose Built for Real-time Analytics
Dashboard and Reporting
Keep dashboards and reports aligned with live data. Every Kafka topic is instantly available in Iceberg, so teams can query fresh events without waiting for pipelines to finish.
Machine Learning & AI
Models are never stale. Feature stores and predictions are updated with the most recent data while retaining the full history.
Unified Governance
We carry Kafka's metadata, schema rules, and access controls through into Iceberg so the data lake stays clean, trustworthy, and auditable.
Data Science Exploration
Queries combine last second activity with years of history in one place. Data scientists can join and analyse streams with accuracy and freshness guaranteed.
What a Unified Kafka + Iceberg View Enables
Structured Table From Raw Kafka
Kafka topics become clean, query-ready tables - translated at read time for fast analytic scans, no repartitioning required.
The Freshest Data
The moment data lands in Kafka, it is queryable in Iceberg. Dashboards, investigations and AI/ML models always stay in step with the stream.
Single Source of Truth
Kafka's access rules, ACLs and retention windows carry over directly. The same policies apply whether you query a second ago or a year back.
Simplified Operations
No compaction jobs, no snapshot cleanup, no repartition rewrites. Data stays in Kafka, and Iceberg is just a logical view.
Stream Processors Give You Speed, But Not Insights.
OLAP databases provide insights, but never in real time. Streambased combines both: the immediacy of stream processing with the depth of analytics.
| Capability | Streambased | OLAP DB | Stream Processors |
|---|---|---|---|
| Real-time data | |||
| Historical view | |||
| Low latency | |||
| Scalable SQL | limited |
Plug directly into your existing stack
Integrate directly with Kafka and analytics tools and move from data to action instantly.
Insights Hub
Stay ahead with perspectives on real-time analytics, streaming architectures, and industry trends.
Three problems, one solution
Streambased unifies Kafka and Iceberg into a single, queryable view, live and historical data together, without moving or copying anything. That one capability can answer a wide range of different data challenges.
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