End-to-End Data Management for Analytics

Panoply.io is a cloud-based data management platform for analytics that streamlines time and value for data engineers, scientists and analysts – automating the full data stack without the overhead of preparing and modeling data, or managing infrastructure – cutting down development time by 80%

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Big Data Simplified

No schema, no modeling, and no configuration. Panoply.io utilizes machine learning and natural language processing (NLP) to automate standard data management activities – saving thousands of code lines, and countless hours of debugging and research.

Any Data. Any Tool. Any Scale

With its ETL-less integration pipeline, Panoply.io connects to all sorts of structured and semi-structured data sources – absorbing billions of writes daily without a line of code and seamlessly working with any analytics tool, from dashboarding to business intelligence and data mining. It’s all a click away.

Forget about the Infrastructure

Panoply.io handles the infrastructure while giving you full control. With its fully managed, end-to-end cloud platform, Panoply.io allows you to capture, process, store, and analyze all your data at lightning speed.

Optimize ROI at Scale

Panoply.io was built to make Big Data accessible, simple, and affordable. Its auto-scaling algorithms learn how to best distribute data across storage technologies while continuously optimizing schema and query configurations, reducing costs while enhancing performance.

Connect Smoothly to the Tools You Love

Panoply.io supports over 60 out-of-the-box integrations with popular data sources and BI tools – from external APIs and proprietary SDKs to tools like Periscope, Looker, and R.

The integration took literally minutes, and presto! We got a fully automated data warehouse running over Redshift. Panoply.io enabled us to transform our production data into actionable insights instantly. Almost zero coding was required in order to pull the data and connect our BI tools.

Ami Goldenberg, Co-Founder and CTO

From raw data to analysis in under 10 minutes.

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