Release Notes for 1.26 Release - August 2026

Calibo Accelerate now uses usage analytics to understand platform usage patterns and identify opportunities to improve user experience and overall platform performance.

Manage your analytics preferences: Analytics collection is optional. If you do not want your platform usage data to be collected for analytics, you can turn off the Analytics toggle in Cookies Preferences. Your choice does not affect your ability to use the Calibo Accelerate platform.

Calibo now supports PostgreSQL and Databricks Unity Catalog as connection types for dbt transformation pipelines.

When configuring a dbt pipeline, users can select either connection type, provide and validate the required connection details, and use the configured connection in the dbt workflow.

This enhancement expands the connectivity options available for dbt transformation pipelines and enables users to integrate PostgreSQL and Databricks Unity Catalog into their dbt workflows.

File uploads for Unity Catalog Volumes instead of DBFS. These are supported for the following source types:

• CSV

• Parquet

• MS Excel

This enhancement provides flexible and supported storage options for uploading files when using Databricks deployed on GCP and Unity Catalog Volumes for file storage.

Calibo Accelerate now allows you to compare any two versions of an MVD side by side from the MVD Details screen. The comparison view clearly shows the source and target versions and highlights added, modified, and not available fields.

This enhancement makes it easier to review changes between MVD versions, improving transparency and review efficiency. It helps in the approve and certify steps or consuming an updated MVD. The comparison view is read-only and does not allow modifications.

Calibo Accelerate now provides visibility into how data assets are used across data pipelines. Usage metrics are available in asset details, helping you understand where data assets are used across pipelines.

You can also reuse existing data assets in data pipelines, making it easier to use trusted data assets across multiple pipelines.

This enhancement improves data asset discoverability, provides greater visibility into data asset usage, and promotes the reuse of existing data assets across data pipelines.

Calibo Accelerate now supports machine learning-based anomaly detection for Analyzer Rules in the DQ Processor node for supported Databricks Unity Catalog environment.

During pipeline execution, Calibo analyzes analyzer metrics, compares actual values with ML-generated predictions, and identifies anomalies and their severity. This eliminates the need to define static thresholds. Anomaly results are stored with the analyzer metrics and are available in the DQ dashboard for visualization and reporting.

To continuously improve prediction accuracy, Calibo Accelerate also introduces dedicated ML Model Training/Retraining capabilities. The model can be automatically retrained at configurable run intervals or manually retrained based on user feedback provided during anomaly review.

By combining statistical analysis, machine learning predictions, and user feedback, the anomaly detection capability helps improve detection accuracy over time and provides actionable insights into data quality trends through the DQ dashboard.

The Calibo Accelerate Orchestrator Agent now supports IAM Roles for Service Accounts (IRSA) for securely accessing secrets stored in AWS Secrets Manager when deployed on Amazon EKS.

With this enhancement, you can configure an IAM role for the Orchestrator Agent pod and associate it with the Kubernetes service account used by that pod. The IAM role can be granted granular permissions to access the required AWS Secrets Manager secrets, eliminating the need to provide AWS credentials directly to the pod.

Calibo Accelerate now supports Google Cloud Platform (GCP) in addition to existing AWS and Azure support. As part of this enhancement, you can:

• Deploy the Calibo Accelerate Orchestrator Agent on Google Kubernetes Engine (GKE) using mutual TLS (mTLS).

• Use Google Cloud Secret Manager to securely store and retrieve credentials for applicable tools in your GCP environment.

This enhancement provides greater flexibility for organizations using Google Cloud and enables them to integrate Calibo Accelerate with their existing GCP infrastructure and security controls.

Web/API technologies can now be deployed on Google Kubernetes Engine (GKE) clusters, extending Kubernetes deployment capabilities to Google Cloud Platform along with the existing AWS and Azure support.

This enhancement provides consistent deployment experience across supported cloud providers while enabling organizations to use GKE for their Web/API workloads.