Enterprise Systems Integration: Snapping Together Multiple Applications and Data Sources 

As enterprise systems grow into agglomerations of cloud applications and big data sources spread across hybrid and even multi-cloud environments, the task of extracting data from many sources and utilizing it within integrated applications consumes increasing time and energy from data architects struggling to map thousands of data elements within a complex data schema tree.

SnapLogic, which says it has the industry’s first unified data and application integration platform as a service (iPaaS), announced their quarterly SnapLogic Elastic Integration Platform that includes additions to its library of more than 400 “intelligent connectors” (called “Snaps”) and enhanced functionality and data governance features for hybrid deployments. Snaps are modular components for a particular data source and applications that are designed to simplify integration by abstracting the complexity of the underlying system.

The privately held company, which was founded in 2006, has more than 400 customers (e.g., CapitalOne, GameStop, Adobe, McKinsey & Company, Yelp) and has attracted nearly $100 million in investment capital, seeks to lower the barriers between data and application integration in the enterprise with a platform built both for self-service and for advanced developers.

SnapLogic's Craig Stewart

According to Craig Stewart, vice president product management, the new release addresses the needs of business leaders, who want access to data from critical applications, and of CIOs, concerned with security, compliance and data governance. He said the Snaplogic platform can reduce integration projects that can takes months to do manually to weeks or days.

“The real thing that we’ve done with our technology,” Stewart told EnterpriseTech, “is what we call the Snaplex, the scalable data processing engine within our platform that’s made up of multiple independent nodes that can then work together as the execution engine for any task. The customer can scale those as they want across multiple nodes. What we’ve done is also made that a YARN application so that in the context of a Hadoop cluster, the scale can be provided by YARN itself so that as there is increasing demand for compute resources the processor will then request of YARN access to additional nodes and it will elastically scale across the Hadoop cluster, scaling out and in automatically.”

SnapLogic said the new release introduces several enhancements to its support for Hadoop- and Spark-based big data integration, including Snaps for:

• Apache Hive data warehouse, which automates execution of Data Manipulation Language (DML) and Data Definition Language (DDL) statements for rapid queries on either Cloudera- or Hortonworks-based Hadoop clusters.
• Teradata, connecting a Teradata database as part of an integrated data pipeline for business analytics.

In addition, the company announced enhanced encryption for “Hadooplex,” SnapLogic’s data processing engine deployed on a Hadoop cluster; the enhancements allow cloud service and database credentials to be stored and encrypted without leaving the SnapLogic environment. The company also announced updates to the Snap for the Anaplan project planning platform, Tableau, Google BigQuery, Google Analytics and NetSuite.