Introduction to Big Data Formats: Understanding Avro, Parquet and ORC
Innovative, data-centric companies are increasingly relying on big data formats like Avro, Parquet, and ORC. These formats are optimized for performing queries and minimizing costs. Companies use them to power machine learning, advanced analytics, and business processes. They’re common inputs into big data query tools like Amazon Athena, Spark, and Hive.
But what exactly are Avro, Parquet, and ORC? How do you decide which of these formats is right for the job? And what do you do when your data is not in the optimal format? If you’re not a database expert, the choices and nuances of big data formats can be overwhelming.
To gain a comprehensive introduction to Avro, Parquet, and ORC, download the 12-page Introduction to Big Data Formats whitepaper. After reading the paper, you will understand:
- Why different formats emerged, and some of the trade-offs required when choosing a format
- The evolution of data formats and ideal use cases for each type
- Why analysts and engineers may prefer certain formats—and what “Avro,” “Parquet,” and “ORC” mean!
- The challenges involved in converting formats and how to overcome them
Plus, learn a flexible framework to help you evaluate which format is right for you.