# 30th March 2023

## Summary

The 30th March 2023 release of e6data includes the following features & enhancements:

* [Single Sign-On (SSO) via AWS SSO, Okta & SAML 2.0 ](#single-sign-on-sso-via-aws-sso-okta-and-saml-2.0)
* [Support for AWS S3 Gateway Endpoints](#support-for-aws-s3-gateway-endpoints)
* [Dynamic Filtering with Date and Timestamp Columns](#dynamic-filtering-with-date-and-timestamp-columns)
* [Parquet Page-level Data Skipping/Pruning](#parquet-page-level-data-skipping-pruning)
* [Distribution Enhancements](#distribution-enhancements)

## Usage Notes

To get access to all features from this release:

* [Update Workspaces](https://docs.e6data.com/product-documentation/~/revisions/W5MExJCuvHiG1ioEcgOy/release-notes-and-updates/broken-reference)
* [Update Clusters](https://docs.e6data.com/product-documentation/~/revisions/W5MExJCuvHiG1ioEcgOy/clusters/edit-and-delete-clusters) to v0.6.12

## Platform Release Notes

### Single Sign-On (SSO) via AWS SSO, Okta & SAML 2.0 

e6data now supports federated authentication using the following Identity Providers (IdP):

* AWS SSO
* Okta
* Other SAML 2.0 compliant IdPs

More information: [Single Sign-On](#single-sign-on-sso)

### Support for AWS S3 Gateway Endpoints

AWS S3 Gateway Endpoints provide reliable connectivity to Amazon S3 without requiring an Internet gateway or a NAT device in a VPC. There is no additional charge for using gateway endpoints. It will provide the ability to route the S3 traffic within the AWS network.

## Engine Release Notes

### Dynamic Filtering with Date and Timestamp Columns

Performance improvements in queries where joins on Date and Timestamp columns are used.

### Parquet Page-level Data Skipping/Pruning

Filtering based on filter conditions that can be pushed down and dynamic filters is now supported.

This improves the performance of queries where a full-row group is narrowed down to a small subset.

### Distribution Enhancements

e6data currently supports distributing:

* Table Scans
* Filters
* Joins between Small Tables
* Aggregations

This particularly benefits queries with a high degree of parallelism i.e a large number of files or row groups to be scanned in any part of the query.

The benefit is proportional to the number of executors/instances participating in the distribution.

The following distributions will be supported in future releases:

* Queries with Windowing functions
* Joins between Big Tables