# real-time lakehouse architecture

Published articles for real-time lakehouse architecture.

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## Build a real-time lakehouse architecture with Redpanda and Databricks

DevFeed: [Build a real-time lakehouse architecture with Redpanda and Databricks](<https://devfeed.tech/articles/build-a-real-time-lakehouse-architecture-with-redpanda-and-databricks-12736.md>)

Original publisher: [Read original article](<https://www.redpanda.com/blog/real-time-lakehouse-databricks-iceberg>)

Author: Peter Henn

Published: 2026-01-06T00:00:00Z

Content type: article

Language: en

Sources: [Redpanda](<https://devfeed.tech/sources/redpanda.md>)

Topics: [Apache Iceberg](<https://devfeed.tech/topics/apache-iceberg.md>), [real-time](<https://devfeed.tech/topics/real-time.md>), [databricks](<https://devfeed.tech/topics/databricks.md>), [Streaming](<https://devfeed.tech/topics/streaming.md>), [data](<https://devfeed.tech/topics/data.md>), [Cloud](<https://devfeed.tech/topics/cloud.md>)

Tags: [analytics](<https://devfeed.tech/tags/analytics.md>), [apache-iceberg](<https://devfeed.tech/tags/apache-iceberg.md>), [cloud-native](<https://devfeed.tech/tags/cloud-native.md>), [databricks](<https://devfeed.tech/tags/databricks.md>), [governance](<https://devfeed.tech/tags/governance.md>), [platforms](<https://devfeed.tech/tags/platforms.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [real-time-lakehouse-architecture](<https://devfeed.tech/tags/real-time-lakehouse-architecture.md>)

### AI overview

This article explains how Redpanda and Databricks can support a real-time lakehouse architecture in which streaming data flows directly into governed, analytics-ready tables. It presents Apache Iceberg as the open, cloud-native table foundation that combines data-lake flexibility with warehouse-style governance and reliability, while describing how this approach reduces batch processing and operational complexity.

### Source excerpt

Learn how Redpanda's Iceberg Topics and Databricks Unity Catalog enable real-time, analytics-ready tables without batch, orchestration, or babysitting.

## Redpanda 25.2: Advancing Iceberg integrations for the real-time lakehouse

DevFeed: [Redpanda 25.2: Advancing Iceberg integrations for the real-time lakehouse](<https://devfeed.tech/articles/redpanda-25-2-advancing-iceberg-integrations-for-the-real-time-lakehouse-12663.md>)

Original publisher: [Read original article](<https://www.redpanda.com/blog/25-2-advancing-iceberg-integration>)

Author: Matt Schumpert

Published: 2025-08-05T00:00:00Z

Content type: article

Language: en

Sources: [Redpanda](<https://devfeed.tech/sources/redpanda.md>)

Topics: [Apache Iceberg](<https://devfeed.tech/topics/apache-iceberg.md>), [real-time](<https://devfeed.tech/topics/real-time.md>), [AWS Glue](<https://devfeed.tech/topics/aws-glue.md>), [databricks](<https://devfeed.tech/topics/databricks.md>), [Event-Streaming](<https://devfeed.tech/topics/event-streaming.md>), [interoperability](<https://devfeed.tech/topics/interoperability.md>), [Streaming](<https://devfeed.tech/topics/streaming.md>), [migration](<https://devfeed.tech/topics/migration.md>), [Kafka](<https://devfeed.tech/topics/kafka.md>), [data](<https://devfeed.tech/topics/data.md>)

Tags: [analytics](<https://devfeed.tech/tags/analytics.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [aws-glue](<https://devfeed.tech/tags/aws-glue.md>), [aws-glue-catalog-integration](<https://devfeed.tech/tags/aws-glue-catalog-integration.md>), [databricks](<https://devfeed.tech/tags/databricks.md>), [databricks-unity-catalog-integration](<https://devfeed.tech/tags/databricks-unity-catalog-integration.md>), [event-streaming](<https://devfeed.tech/tags/event-streaming.md>), [iceberg-capabilities](<https://devfeed.tech/tags/iceberg-capabilities.md>), [integration](<https://devfeed.tech/tags/integration.md>), [interoperability](<https://devfeed.tech/tags/interoperability.md>), [kafka](<https://devfeed.tech/tags/kafka.md>), [kafka-json-schema-mapping](<https://devfeed.tech/tags/kafka-json-schema-mapping.md>), [low-latency](<https://devfeed.tech/tags/low-latency.md>), [migration](<https://devfeed.tech/tags/migration.md>), [open-source-ai-connectors](<https://devfeed.tech/tags/open-source-ai-connectors.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [real-time-data-lakes](<https://devfeed.tech/tags/real-time-data-lakes.md>), [real-time-lakehouse-architecture](<https://devfeed.tech/tags/real-time-lakehouse-architecture.md>), [redpanda-25-2-release](<https://devfeed.tech/tags/redpanda-25-2-release.md>), [redpanda-iceberg-integration](<https://devfeed.tech/tags/redpanda-iceberg-integration.md>), [schema-registry-authorization](<https://devfeed.tech/tags/schema-registry-authorization.md>), [streaming-data-analytics](<https://devfeed.tech/tags/streaming-data-analytics.md>), [streaming-platform-updates](<https://devfeed.tech/tags/streaming-platform-updates.md>), [vendor-lock-in](<https://devfeed.tech/tags/vendor-lock-in.md>)

### AI overview

Redpanda 25.2 expands Iceberg integration for a real-time open lakehouse architecture. It adds integrations with Databricks Unity Catalog and AWS Glue Catalog, supports AWS Glue as an Iceberg REST Catalog for Redpanda Iceberg Topics, and expands schema support. The release also includes migration improvements from Confluent and Schema Registry Authorization updates, while emphasizing Kafka client compatibility, low-latency ingestion, open interoperability, and reduced vendor lock-in.

### Source excerpt

Check what's new in Redpanda 25.2 as we expand our Iceberg capabilities, delivering on the promise of a real-time open lakehouse architecture.