That export is a starting point.
Bring CSV, JSON, and Parquet files into Lake. Turn large exports into datasets you can explore alongside the rest of your business data.
Bring fragmented data together, analyze beyond database limits, and scale from gigabytes toward petabytes — one analytical foundation.
01Bring fragmented data together
Your next answer might be hiding between a customer table, a payment export, and years of orders. Give them a place to meet.
Bring CSV, JSON, and Parquet files into Lake. Turn large exports into datasets you can explore alongside the rest of your business data.
Connect purchase history with customer records to explore repeat purchases and lifetime value.
Yesterday's transactions become tomorrow's context. Keep historical data ready for comparisons, cohorts, and the questions you haven't asked yet.
02Analyze without the database limits
Your application has customers to serve. Bring datasets into Lake and give heavy scans, joins, and aggregations a separate place to run.
Operational work stays with your app.
Analytical work runs on datasets in Lake.
Explore large transaction histories and event datasets. Look beyond the slice of data that fits in a spreadsheet.
Compare periods, investigate a spike, or join another dataset. Build your analysis around the question you're asking.
Run analysis on data brought into Lake so those analytical queries don't compete with your application's everyday workload.
03Scale from GB to PB
Start with today's exports. Add more sources, more history, and more ambitious questions. Lake is designed to grow from gigabytes toward petabyte-scale datasets.
HOW BIG IS YOUR NEXT CHAPTER?
Start with exports, customer tables, and the question you need to answer today.
Designed to scale from GB toward PB.
Compare years, not just the last 30 days. Give long-term patterns time to emerge.
Build on the datasets you already have as new sources become part of your business.
Keep your analytical work together as data volumes and the questions you ask grow.
Your first dataset is just the beginning.
Join the waitlist for early access.