SnapLogic harnesses AI to build end-to-end integrations; improve connectivity with Salesforce, Coupa, and Delta Lake by Databricks

SnapLogic introduced a new breakthrough AI capability to help citizen and expert integrators complete integrations faster and more easily, boosting user productivity and enabling IT and development teams to focus on more strategic, high value tasks. 

The new feature, called Pipeline Synthesis, leverages SnapLogic’s machine learning-based engine, Iris AI, to infer user intent and organizational insight to instantly build and suggest new, complete, end-to-end integration pipelines to solve an integration task at hand. 

In addition to the new Pipeline Synthesis feature, the November 2019 release of the SnapLogic Intelligent Integration Platform also includes additional Iris AI enhancements, new Kubernetes support, and enhanced connectivity with Salesforce, Coupa, and Delta Lake by Databricks.

New and enhanced capabilities in this month’s release of the SnapLogic Intelligent Integration Platform advance usability, connectivity, and performance for customers. 

The update will provide an enhanced Mapper AutoLink function that simplifies source-to-target mappings and provides relevance scoring highlighting the accuracy of mappings, improving productivity for less technical users. In addition, the release includes improved algorithms to support the development of pipelines with multiple endpoints. 

Customers can now integrate the deployment of Snaplexes in their Kubernetes-based DevOps processes allowing Snaplexes to be spun up as needed to manage their infrastructure.

Organizations can now designate critical pipelines to be part of automated regression testing. Users will get a report on pipeline behavior before and after a new SnapLogic platform release, giving them the assurances they need to upgrade with ease and confidence. This release adds support for Delta Lake, the open source storage layer created by Databricks, to help data engineers build high quality, reliable data lakes for improved analytics. 

New capabilities to modify API proxies and customize the API developer portal drive productivity gains for API Managers; with enhancements made to some of the more popular Snaps, including Salesforce, Coupa, Snowflake, and PostgreSQL to help drive greater connectivity and value for customers.

The release of the SnapLogic Intelligent Integration Platform is immediately available to all customers.

SnapLogic extends alliance with Databricks to boost data lake reliability; analyze big data workloads in the cloud

SnapLogic has expanded its partnership with Databricks with new support for Delta Lake, the open source storage layer created by Databricks that brings reliability to traditional data lakes. 

Together, the joint solution helps customers accelerate the integration, transformation, and processing of big data workloads into Delta Lake, increasing data quality and accelerating the time to value of advanced analytics and machine learning initiatives.

Delta Lake provides ACID transactions, scalable metadata handling, and unifies streaming and batch data processing. Delta Lake runs on top of existing data lake and is fully compatible with Apache Spark APIs. Delta Lake on Databricks allows users to configure Delta Lake based on their workload patterns and provides optimized layouts and indexes for fast interactive queries.

Delta Lake sits on top of Apache Spark. The format and the compute layer helps to simplify building big data pipelines and increase the overall efficiency of the pipelines.

Organizations are increasingly investing in data lakes to gain actionable insights into their growing data assets. However, the high volume and complexity of data often results in data quality, reliability and performance issues. 

Together, SnapLogic and Databricks are removing these roadblocks by providing a low-code, visual paradigm for data engineers to create and process data pipelines that leverage the full power of Delta Lake — including features like ACID transactions, scalable metadata handling, schema enforcement, and batch and streaming support.

“Databricks and SnapLogic are committed to delivering product innovations that help organizations reduce the time, effort, and skills needed to manage their big data initiatives so they can quickly turn their data into meaningful insights that drive the business forward,” said Craig Stewart, chief technology officer, SnapLogic. “By teaming up with Databricks, we aim to remove the key technical barriers to data lake and big data management so our customers can accelerate their analytics and machine learning initiatives and focus on delivering real business value.”