Real-time, high-volume data streaming and reliable data storage
Parse.ly’s Data Pipeline enables your team to analyze and act on large amounts of granular content data as it’s generated. We’ll keep that data around so you can do historical analysis, too.
Perform custom analysis with tools you already use
We’ll fit right into your analytics stack, letting you store, format, and query your data however you want. Get started on finding answers instead of learning a new tool.
Save time on your pipeline
We clean and transform the data for you, so your BI and Data Science teams can focus on analysis.
What customers are saying
Parse.ly offers us a pretty unique view of our active subscribers because we don’t have any other tools that actively track of retention.
We can see what types of stories subscribers are reading, how much time they’re spending on the site, and what referral sources they come from.
Indu Chandrasekhar Director of Audience Development, WIRED
Companies using Parse.ly every day
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What tools does Parse.ly’s Data Pipeline work with?
The data formats we developed are especially easy for Python, R, Spark, Redshift, BigQuery: you name it. We also have standard integration schemas and recipes so that the data can be used in ad-hoc querying and dashboarding tools, such as Looker, Periscope, and Tableau.
Do I own the data used by the Parse.ly platform?
Yes! The pipeline delivers you 100% of your raw, unsampled data. You get a stream with a firehose of every single event from your users, sites, and apps. Data is delivered fast: with end-to-end delivery times measured in seconds. You also get an elastic data store for full historical retention, stored in 15-minute chunks of compressed JSON data. It’s neatly organized and can go back for weeks, months, or years. There are no rollups. Every single event is captured, then stored securely and durably.
Who can use Parse.ly’s Data Pipeline?
Multiple teams including Business Intelligence teams, SQL experts, data scientists, data engineers, and product teams can all use the Parse.ly Data Pipeline to gather insights.
