No schema, no modeling, no configuration. Panoply utilizes machine learning and natural language processing (NLP) to learn, model and automate the standard data management activities performed by data engineers, server developers and data scientists, saving thousands of code lines and countless hours of debugging and research.
With its ETL-less integration pipeline, Panoply connects to all sorts of structured and semi-structured data sources – absorbing billions of writes daily without a line of code, and allowing you to capture and process your data at lightning speed.
Panoply supports dozens of out-of-the-box integrations with popular Big Data and BI tools – from external APIs and proprietary SDKs to tools like Periscope, Looker, and R.
One of the biggest challenges of running a data warehouse in a high-growth company is having to continuously manage capacity and performance as schemas and workloads rapidly evolve. Panoply's machine learning based data warehouse management saves a lot of time spent on maintenance and trial-and-error tuning, allowing data engineers to focus on helping deliver business insights.