Announcing Imply 3.1

by Vadim Ogievetsky · September 26, 2019

We are delighted to announce that Imply 3.1 is now available! Imply 3.1 is based on Apache Druid 0.16 and contains many improvements.

**Don’t miss the Imply 3.1 / Druid 0.16 webinar where I’ll demonstrate the new features and you can ask me anything. **

Druid powerhouse

This Imply release is based on Druid 0.16.0, a release so feature-rich and magnificent that it deserves a post of its own. At a glance, Druid 0.16.0 contains major performance, ingestion, and web console improvements:

  • Query vectorization, speeding up many queries by 1.3–3x
  • Shuffle for native parallel batch ingestion, boosting the power and flexibility of native (non-Hadoop-based) batch ingestion
  • An Indexer process, simplifying deployment configuration and architecture
  • Point-and-click stream ingestion and SQL workbench in Druid’s web console

Material refresh

In this release we have done a number of UI tweaks to make the interface feel smoother and more user friendly.

Embeddable visualizations

It is now possible to embed any visualization within your own application. With the embedding mode enabled simply grab the code for the visualization iframe and paste it wherever you want.

It is now possible to control an embedded Pivot iframe completely via the HTML5 postMessage API

Point-and-click data reindexing

In this release we are adding the ability to reindex data in Druid using the point-and-click data loading wizard, allowing you to modify your data in Druid with ease.

Reindexing can be used to ‘drop’ sensitive rows from the data or to adjust the columns to manipulate the data footprint. This can all be done now without writing any JSON by hand.

OIDC integration

This release greatly expands Pivot’s SSO support beyond just Okta to fully support any custom OIDC provider. It is now also possible to map OIDC groups to Imply roles.

Improved access control

This release also adds new features for managing how users can share and edit content in Pivot. User and role admins can now limit sharing by role, and it is now possible to grant limited, fine-grained edit privileges on data cubes.

Back to blog

How can we help?