ODP 3.3.6.3-1, 3.2.3.5-2, and 3.2.3.5-3 are now available

Modern data platforms have to evolve continuously—without turning every improvement into a disruptive migration. Security expectations keep rising. Many organizations are operating in hybrid environments. Orchestration needs to scale. And platform upgrades (especially Java) can easily become high-risk projects.

That’s what drove ODP 3.3.6.3-1, ODP 3.2.3.5-2, and ODP 3.2.3.5-3: helping teams modernize safely—move forward on JDK 17 and JDK 11, strengthen security and secret handling, improve S3-backed reliability for Hive and Hadoop, scale Airflow orchestration, and increase flexibility for Spark and Livy runtimes.

Acceldata Open Data Platform (ODP) is an enterprise-ready open data platform built on a secure, flexible foundation—bringing together core open source technologies so teams can standardize and modernize big data environments across on-prem and hybrid deployments.

At a glance: what’s in each release line

ODP 3.3.6 release line — ODP 3.3.6.3-1

Best for teams moving toward JDK 17, with flexibility in how you standardize Java across environments.

• JDK 17 certification across the 3.3.6 release line (JDK 11 certification continues)
• Ambari v3.0.0.0-1 and security hardening with standardized password encryption using the native credential store helper
  (Note: Ambari itself requires JDK 17 at runtime; the ODP stack can use JDK 11 or JDK 17.)
• Pinot upgrade: v1.3.0 → v1.4.0
• Enhancements, component upgrades, bug fixes, and CVE updates

ODP 3.2.3 release line — ODP 3.2.3.5-2 and ODP 3.2.3.5-3

Best for teams standardizing on JDK 11 and improving hybrid operations and runtime flexibility.

• JDK 11 certification across the 3.2.3 release line
• Improved S3 support for Hive and Hadoop, including extended S3 delegation token features
• Airflow orchestration enhancements with Redis integration and multi-node support
• Multi-version Spark 3 + Livy 3 minor-version coexistence in the same ODP environment
• Technical Preview: Ranger extension for AWS-S3
• Note: ODP 3.2.3.5-2 is the Python 2 release; ODP 3.2.3.5-3 is the Python 3 release

Highlights

Certified JDK 11 support across the 3.2.3 release line

Java upgrades often get delayed because they can ripple into broader platform change. With this release line, JDK 11 is certified across ODP 3.2.3, so you can adopt Java 11 with a predictable path—without introducing unnecessary platform churn.

What you gain

• A cleaner modernization path for Java 11
• Reduced upgrade risk from unnecessary platform changes
• Easier standardization for enterprise environments that need consistent baselines

Certified JDK 17 support across the 3.3.6 release line

With this release line, JDK 17 is certified across ODP 3.3.6, so you can adopt Java 17 with a predictable path—without introducing unnecessary platform churn.

What you gain

• A cleaner modernization path for Java 17
• Reduced upgrade risk from unnecessary platform changes
• Easier standardization for enterprise environments that need consistent baselines

Upgraded Ambari and hardened security with consistent secret handling

Security is easier to operate (and govern) when encryption and credential handling are standardized. This release strengthens Ambari by standardizing password encryption using the native credential store helper—improving consistency and long-term maintainability for authentication and secret management.

What you gain

• Ambari upgraded to 3.0.0.0-1 in the 3.3.6 line (Ambari runtime on JDK 17)
• More consistent governance across clusters
• Less operational drift over time
• Easier day-2 operations for security teams and platform operators

More reliable S3-backed workloads for Hive and Hadoop

As more analytics and pipeline workloads rely on object storage, reliability and secure access patterns matter more—especially for long-running jobs and hybrid architectures. This release improves Hive and Hadoop S3 integration, including support for extended S3 delegation token features, to strengthen secure and reliable S3-backed execution.

What you gain

• More reliable access patterns for S3-backed workloads
• Better support for enterprise credential approaches
• Fewer surprises as cloud-connected usage grows

Scalable orchestration with Airflow (Redis + multi-node support)

Orchestration can become a bottleneck as pipeline volume grows. This release introduces Airflow enhancements including Redis integration and multi-node deployment support, helping teams scale orchestration more cleanly.

What you gain

• Better scalability as DAGs, teams, and workloads grow
• Stronger foundations for more resilient orchestration deployments
• Reduced bottlenecks as orchestration becomes a shared service

More flexibility with Spark and Livy minor versions in one environment

Not every team can upgrade runtimes on the same schedule—and forcing it creates friction. This release introduces support for multiple Spark 3 and Livy 3 minor versions coexisting in the same ODP environment.

What you gain

• Easier upgrades (teams don’t all need to move at once)
• Better workload isolation
• Less environment sprawl (fewer separate clusters to manage)

Technical Preview: Ranger extension for AWS-S3

For teams exploring deeper governance controls for object storage access, this release includes a Technical Preview of a Ranger extension for AWS-S3.

Pinot upgrade (v1.3.0 → v1.4.0)

ODP 3.3.6.3-1 upgrades Apache Pinot to v1.4.0, bringing performance, stability, and operational improvements to real-time analytics workloads.

Why this matters

• Move forward on real-time analytics as part of your platform lifecycle (not as a separate upgrade project)
• Adopt newer Pinot capabilities with a cleaner operational path through the ODP release line

Enhancements, upgrades, fixes, and CVE updates

Alongside the headline capabilities above, ODP 3.3.6.3-1, ODP 3.2.3.5-2, and ODP 3.2.3.5-3 also include component upgrades, platform enhancements and optimizations, plus bug fixes and CVE fixes to improve stability and reliability.

Learn more

Release notes: ODP 3.3.6.3-1, ODP 3.2.3.5-2, ODP 3.2.3.5-3

Learn more about Open Data Platform (ODP).

Book a free consultation to see how ODP fits your environment and helps with your modernization roadmap.