How to combine data from Hortonworks with Gnip

Pipes allows you to quickly Integrate Hortonworks with Gnip data for a combined analysis.
Load data from Hortonworks and Gnip into your central data warehouse to analyze it with the business intelligence tool of your choice.
Pipes allows you to connect to Hortonworks, Gnip, and more than 200 other APIs, web services, and databases with ready-to-use data connectors. Automate your data workflows through data pipelines without a single line of code.
1

Connect your data warehouse

It will be the destination of all data pipelines you build. Pipes supports relational databases in the cloud and on-premises.
2

Connect to Hortonworks and Gnip

You just need to enter the associated credentials to allow Pipes access to the Hortonworks API and the Gnip API.
3

Combine data from Hortonworks and Gnip

Pipes lets you select the data from Hortonworks and Gnip that you want to load to your data warehouse. These data pipelines will run automatically on your defined schedule!

About Hortonworks

Hortonworks focuses on the development of Apache Hadoop and related Apache projects. The connected data suite solutions offered by Hortonworks deliver end to end capabilities for data-in-motion and data-at-rest.

About Gnip

Gnip provides social media API aggregation to collect data from different social media channels via a single API. The Gnip Data Collector that ways helps companies to simultaneously collect social data from multiple public APIs thus to simplify and save on their resources.

Your benefits with Pipes

Get central access to all your data

Access data from 200+ data sources with our ready-to-use connectors and replicate it to your central data warehouse.

Automate your data workflows

Stop manually extracting data and automate your data integration without any coding. We maintain all pipelines for you and cover all API changes!

Enable data-driven decision-making

Empower everyone in your company with consistent and standardized data, automate data delivery and measure KPIs across different systems.