In an ecosystem where control and seamless data flow are becoming essential to performance management, Pigment is taking a new strategic step forward. The vendor announces the availability of its native integration with Databricks, based on the Delta Sharing protocol, enabling organisations to connect their Databricks tables directly to their Pigment business applications. A major development for all finance and operations teams seeking to improve data reliability and accelerate their analyses.
A direct bridge between Databricks and Pigment
Until now, companies connecting these two platforms had to rely on in-house pipelines or third-party connectors. With this new capability, Pigment now offers a fully integrated and secure connector based on Delta Sharing, the open protocol developed by Databricks to facilitate cross-platform data sharing.
In practice, Databricks teams define a Share containing the tables to be exposed, create a Recipient representing Pigment, then generate a credentials file. Once imported into Pigment, this file activates a direct connection that can be used from any authorised Application.
Simplified setup, designed for business teams
On the Pigment side, activation is carried out directly from the Integrations area, accessible to Workspace administrators. The Databricks Delta Sharing connector now appears alongside the platform's other native integrations. Just a few details are required — connector name, access rights and JSON profile — to make the connection instantly available.
This simplicity is in line with Pigment's philosophy: enabling Finance, HR, Revenue and Supply Chain teams to use reliable data without relying on extensive technical resources. In just a few clicks, a user can import a Databricks table into a transactional list, cube or existing model.
Reliable data available in just a few seconds
Once the connection is activated, the user selects the table to import from those made available in Databricks. Pigment automatically detects the configured Shares, Schemas and Tables. The import takes just a few seconds, provided that the table is under 500 Mo, the threshold imposed by the integration to ensure performance and seamless operation.
This approach unifies the analytics pipeline: data remains in Databricks, where it is governed, cleansed and transformed, while Pigment becomes the central point for modelling, scenario planning and performance management.
Enhanced security and improved governance
To meet the requirements of large enterprises, Databricks also enables the use of tokens to be restricted to specific IP address ranges. Pigment also provides an official list of IP addresses to configure in order to strengthen the security of data exchanges.
This focus on data governance reflects a broader trend: finance departments require secure, audited and standardised connections, far removed from the disparate scripts that are often a source of errors or operational fragility.
A new capability aligned with Pigment's Data & AI strategy
By integrating natively with Databricks — a platform widely used for engineering, machine learning and large-scale analytics — Pigment confirms its ambition to be at the heart of the data ecosystem of modern enterprises.
This integration paves the way for several key use cases:
synchronisation of transactional or historical data,
automated feeding of forecasts and scenarios,
use of models generated in Databricks to enrich Pigment simulations,
harmonisation of master data within a single decision-making hub.
A long-awaited development for Data and Finance teams
This new capability was highly anticipated: many companies are already building their data lakehouse on Databricks. The bridge with Pigment is now official, supported and much easier to use.
With this native connector, Pigment further strengthens its position as a next-generation EPM platform, capable of integrating seamlessly with the Data & AI ecosystem without sacrificing transparency, security or user experience.
source: Pigment
