PARQUET file: How to open? The best software for opening parquet files

Q: How to open parquet file?

To open a .parquet file, you can use software tools like Apache Spark, Apache Drill, or Hive on Windows, Mac, or Linux systems. Data analysis programs such as Pandas with Python also support reading Parquet files through libraries like PyArrow or fastparquet. Specialized tools like Parquet Viewer or Databricks can offer graphical interfaces to view and explore Parquet data.

PARQUET

Columnar storage file format optimized for big data processing.

File type: Database file

The .parquet file format is a columnar storage technology designed for efficient data processing and analysis. It is widely used in big data frameworks such as Apache Hadoop, Apache Spark, and other analytics tools. Files in this format are optimized for read performance and storage efficiency.

What is parquet file?

File type category:
Database file

Date updated: July 19, 2026

Parquet is an open-source columnar storage file format developed to support the efficient storage and retrieval of large datasets. It was created by the Apache Software Foundation as part of the Apache Hadoop ecosystem and has become a standard in big data processing due to its performance advantages.

This format stores data in a column-oriented manner, which allows for more efficient compression and encoding, especially for analytical queries that access only a subset of columns. Parquet files can contain complex nested data structures, making them suitable for various data types and schemas. The format supports multiple compression algorithms like SNAPPY, GZIP, and LZO, further enhancing storage efficiency.

Compatible across multiple platforms and languages, Parquet is supported by popular data processing frameworks such as Apache Spark, Apache Drill, Hive, and Pandas. Its design enables fast querying and retrieval, making it a preferred choice in data warehousing, machine learning, and big data analytics applications.

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How to open parquet file?

To open a .parquet file, you can use software tools like Apache Spark, Apache Drill, or Hive on Windows, Mac, or Linux systems. Data analysis programs such as Pandas with Python also support reading Parquet files through libraries like PyArrow or fastparquet. Specialized tools like Parquet Viewer or Databricks can offer graphical interfaces to view and explore Parquet data.

How to convert parquet file?

Converting other data formats to or from Parquet can be achieved using tools like Apache Spark, PyArrow, or fastparquet in Python. These libraries support reading and writing Parquet files and can be integrated into data pipelines. Online converters for Parquet are limited, but desktop tools and command-line utilities provide reliable options for format conversion. For example, Apache Spark's spark-submit command can convert CSV, JSON, or Avro files into Parquet format efficiently.