How to load your data from Twitter to Snowflake

Pipes allows you to automatically replicate your Twitter data into Snowflake on your defined schedule.
Load all your data from Twitter to Snowflake to instantly get access to your Twitter data. This data will always be updated on your defined schedule.
Pipes allows you to automatically load your Twitter data into Snowflake. With ready-to-use connectors and pre-built data schemas for more than 200 APIs and web services you build data pipelines in minutes and without any coding. ​

Connect to Snowflake

This will be the destination of all data pipelines you build. Besides Snowflake, Pipes supports the most used relational databases in the cloud and on-premises.

Connect to Twitter

Just enter your credentials to allow Pipes access to the Twitter API. Then Pipes is able to retrieve your data from Twitter.

Create a data pipeline from Twitter to Snowflake

Pipes lets you select the data from Twitter you want to have in Snowflake. This pipeline will run automatically on your defined schedule!

About Twitter

Twitter is an online social networking and news service that enables users to read and send short 140-character messages called “tweets”. Registered users can both post and read tweets while unregistered users have read access only. Twitter allows user access through the website interface, SMS and with the mobile app.

About Snowflake

Snowflake is a high performing cloud data warehouse. It can either be used to store your data in it or / and to use it as a data source.

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.