Gaining fast, accurate insights from big data has become critical for every business. But if it is difficult or time-consuming to ingest or integrate data from multiple sources, those insights will be delayed. With SnapLogic’s easy-to-use data integration platform as a service (iPaaS), Hortonworks customers are able to quickly ingest, prepare and deliver data, whether the source is on premises, in the cloud or in a hybrid cloud environment.
With powerful data integration transformations, aggregation, joins and sorts as well as intelligent connectors – called Snaps – for Salesforce, Amazon Redshift, SAP, Cassandra, Workday and many more, the SnapLogic Elastic Integration Platform is ideally suited for structured and unstructured data extraction, transformation and loading (ETL) for Hadoop or Spark.
SnapLogic also allows you to make Hadoop and Spark data easily available to off-cluster applications and data stores such as statistical packages and business intelligence (BI) or data visualization tools, with Snaps for tools like Tableau, Birst, Tidemark and more.
Certified Technology Partner
SnapLogic is a Certified Technology Partner on Hortonworks Data Platform (HDP). The Hortonworks Certified Technology Program reviews and certifies technologies for architectural best practices, validated against a comprehensive suite of integration test cases, benchmarked for scale under varied workloads and comprehensively documented.
HDP - HDP Certified badge indicates this partner’s solution has been certified to work with HDP; reviewed for architectural best practices and validated against a comprehensive suite of integration test cases, benchmarked for scale under varied workloads and comprehensively documented.
Yarn Ready - Apache Hadoop YARN is the data operating system for Hadoop 2. YARN Ready certification recognizes applications that integrate with YARN and process data via pushdown computation to the cluster. Examples of a YARN ready solution includes an application that has native YARN application master or leverages scale-out capabilities of the platform like Hive, Spark and MR2.