Spartan Blog - Jerónimo

Spring Batch is one of the few existing tools in the Java Enterprise ecosystem for building batch processes or data pipelines.

This week I released a new version of Carpet, the Java library for working with Parquet files.

A few days ago, the creators of DuckDB wrote the article: Query Engines: Gatekeepers of the Parquet File Format, which explained how the engines that process Parquet files as SQL tables are blocking the evolution of the format.

Apache Parquet is a columnar storage format optimized for analytical workloads, though it can also be used to store any type of structured data solving multiple use cases.

After some time working with Parquet files in Java using the Parquet Avro library, and studying how it worked, I concluded that despite being very useful in multiple use cases and having great potential, the documentation and ecosystem needed for adoption…

This post continues the series of articles about working with Parquet files in Java.

In the previous article, I wrote an introduction to using Parquet files in Java, but I did not include any examples.

Parquet is a widely used format in the Data Engineering realm and holds significant potential for traditional Backend applications.

In previous posts I’ve analyzed Protocol Buffers and FlatBuffers, using JSON as the baseline.

In the previous post I analyzed Protocol Buffers format, using JSON as baseline.