November 13, 2018
Data Platform Products
At PayPal, data engineers, analysts, and data scientists work with a variety of data sources (messaging, NoSQL, RDBMS, documents, TSDB), compute engines (Spark, Flink, Beam, Hive), languages (Scala, Python, SQL), and execution models (stream, batch, interactive).
Due to this complex matrix of technologies and thousands of data sets, engineers spend considerable time learning about different data sources, formats, programming models, APIs, optimizations, etc., which impacts time to market. To solve this problem and make product development more effective, PayPal developed and open sourced Gimel, a unified analytics data platform which provides access to any storage system through a single, unified data API and SQL interface that are powered by a centralized data catalog.
PayPal Notebooks is a package of customizations and enhancements to Jupyter to simplify analytics and modeling, significantly improving the analyst and data scientist agility and productivity.
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