How to combine data from Hive with Gnip

Pipes allows you to quickly Integrate Hive with Gnip data for a combined analysis.
Load data from Hive and Gnip into your central data warehouse to analyze it with the business intelligence tool of your choice.
Pipes allows you to connect to Hive, 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 Hive and Gnip

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

Combine data from Hive and Gnip

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

About Hive

Apache Hive is a data warehouse infrastructure which provides query, data summarization, and analysis, built on top of Hadoop. The Apache Hive data warehouse software facilitates writing, reading, and managing large datasets with distributed storage using SQL. A JDBC driver and command line tool are provided to connect users to Hive.

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.