Product Release Notes - January 2026

Overview

This release introduces deeper integrations for Databricks, enhanced security protocols for enterprise workloads, and expanded lineage support for Snowflake. It strengthens the connector suite for streaming and pipeline platforms and extends Kerberos-backed lineage for Spark, Hive, and Impala, with additional enterprise authentication support for integrated environments.

These updates focus on three areas: advanced cloud data integration, enterprise-grade security, and robust pipeline connectivity.

Enterprise-grade authentication

This release prioritizes support for Cloudera authentication protocols.

• Spark lineage with Kerberos authentication support: Secure Spark lineage using industry-standard Kerberos authentication.

• Secure Hive and Impala Kerberos integration: Supports secure authentication protocols for Hive and Impala integration.

Databricks ecosystem and AI intelligence

This release provides enhanced capabilities for Databricks environments, extending beyond native Databricks lineage functionality.

• Unity Catalog integration: Lowers the barrier to analyzing complex Databricks data catalogs.

  Enhanced Delta Live Tables: Deepened support for Databricks Delta Tables for high-performance ACID transactions and metadata handling.

• Supported lineage for Databricks Notebooks AI outside Unity Catalog: Cloudera Octopai captures lineage for AI notebooks that reside outside Unity Catalog.

• Supporting lineage of Python jobs: Lineage for Python jobs run on the Databricks compute engine.

• Databricks and Hive Metastore (HMS) connector (multiple metastores): Bridges Hive metadata with Databricks environments.

Streaming, connectivity, and lineage

The following updates extend streaming connectors, pipeline connectivity, and lineage for data in motion.

• Snowflake Stage enhancement: Improved support for pipeline lineage, providing end-to-end visibility of data movement into Snowflake.

• Apache Kafka and Kafka Connect: New, robust connectors to support Kafka lineage.

• DataStage Sequencers: Enhanced analysis support for IBM InfoSphere DataStage Sequencer jobs to improve ETL orchestration visibility.

• Apache NiFi connector: Full support for NiFi integration with Apache Knox authentication.

Use cases

These enhancements improve productivity, security, and transparency. By automating manual tasks and strengthening security controls, Cloudera Octopai enables data teams to focus on innovation rather than infrastructure.

• For data engineers and analysts

  • Solving the metadata management chaos: Cloudera Octopai automatically maps the entire lineage across Cloudera and external systems such as Databricks, Oracle, or Snowflake, revealing what data is obsolete versus what is business-critical.

  • End-to-end lineage: With enhanced Databricks and Snowflake Stage support, teams can audit and trace data flow with confidence, simplifying compliance and troubleshooting.

  • Seamless ingestion: Use the new Kafka and NiFi connectors to build real-time pipelines without writing custom code for complex integrations.

• For enterprise security teams

  • Cloudera connector protocols: Five Cloudera connectors enable unified governance that can be enforced using a single governance model that follows the data, regardless of where it is stored or processed.

  • Unified governance: The Databricks connector allows for a single source of truth for metadata, reduces the risk of data silos or partial governance, and surfaces full Databricks lineage—including for assets outside your Cloudera deployment—so you can assess migration success.

Roadmap

Future enhancements planned for upcoming releases:

• Trino integration: Enabling a more holistic UDF solution.

• Microsoft Fabric support.

• Revamped Universal Connector (Connector Factory): Enhanced support for inner-system lineage and frequency refresh.