Feature Releases & Updates

Release Notes: 3/03/2021

As a part of the overall feature and functionality updates to the Ascend Platform, we’ve released a number of improvements and features.

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Release Notes: 2/16/2021

As a part of the overall feature and functionality updates to the Ascend Platform, we’ve released a number of improvements and features.

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New Release: Python SDK

We are excited to announce the release of our new Python SDK! This SDK sits on top of Ascend’s public API, and is dynamically generated based upon the Protocol Buffer and gRPC (which we use extensively) definitions of all components within the Ascend platform. … Read More

New Feature: Dataflow JDBC/ODBC Connector

This feature leverages the same intelligent persistence layer that backs Queryable Dataflows and Structured Data Lakes, and joins it (pun intended) with the SparkSQL Thrift JDBC/ODBC Server to provide the ability to directly access and query your Dataflows from your favorite environment, whether it is a BI tool like Looker, or your favorite SQL workbench. … Read More

New Feature: Scala & Java Transforms

Today we’re excited to formally announce support for Scala & Java transforms. Not only does this expand our support to two of the most popular languages amongst data engineers, but marries this capability with the advanced orchestration and optimizations provided by Ascend. … Read More

New Feature: Credentials Vault

Credentials Vault is a centralized place to store and manage secrets used by your dataflows. The feature makes it even easier to collaborate with others to quickly ingest from, and write to external data systems. It also empowers site administrators with an interface to audit and control all credentials in use by the Ascend platform. … Read More

New Feature: Recursive Transforms

A recursive transform is a transform that uses the output of its previous run as an input into the next run. This pattern is often used to incrementally aggregate data. In cases where historical data is substantially larger than the aggregated data, this pattern can result in significant reduction in processing time and compute resources. … Read More

New: support for 75 more SQL functions

We’re announcing the addition of 75 new SQL functions that are now available in every customer environment by default. This includes powerful new functions like BOOL_AND, COUNT_IF, FIND_IN_SET, MAX_BY, WEEKDAY, and well, 70 more!!! … Read More

Queryable Dataflows: Combining the Interactivity of Warehouses with the Scale of Pipelines

Now in Ascend, all stages of all Dataflows are queryable without switching tools or disrupting your development process. As part of this capability, we’ve built an interactive query editor that lets you interact with Connectors and Transforms in Dataflows, as well as Data Feeds broadcasting from other Data Services, as though they are read-only tables in a SQL database. … Read More

Introducing the Autonomous Dataflow Service!

This week, the team at Ascend is launching our Autonomous Dataflow Service, which enables data engineers to build, scale, and operate continuously optimized, Apache Spark-based pipelines. … Read More