Scale By the Bay 2020

At PayPal, data engineers, analysts, and data scientists work with a variety of data sources (RDBMS, NoSQL, Messaging, Documents, Big Data, Time Series Databases), compute engines (Spark, Flink, Beam, Hive), languages (Scala, Python, SQL) and execution models (stream, batch, interactive) to process petabytes of data. Due to this complex matrix of technologies and thousands of datasets, engineers spend considerable time learning about different data sources, formats, programming models, APIs, optimizations, etc. which impacts time-to-market (TTM). To solve this problem and to make product development more effective, PayPal Data Platforms developed "Gimel", an open source, unified analytics data platform which provides access to any storage through a single unified data API and SQL, which are powered by a centralized data catalog. Join us and learn how to build a unified data platform with Scala and Spark and how to conquer the heterogenous data landscape providing effective solution for many users in the enterprise.