What is PARQUET?

Apache Parquet is a columnar storage format that organizes data by column rather than by row, making it highly efficient for analytical queries that only need specific columns. Unlike CSV or JSON which store data row-by-row, Parquet groups all values of a column together, enabling better compression and faster querying.

Used extensively in big data ecosystems (Spark, Hive, Presto, AWS Athena), Parquet achieves 10x compression compared to CSV and allows queries to skip irrelevant columns entirely. It's the de facto standard for data lakes and analytics pipelines, supporting complex nested data structures and schema evolution.

Did you know? Parquet can compress data 10-100x better than CSV for analytics!

History

Parquet was created by Twitter and Cloudera to bring efficient columnar storage from Google Dremel to the Hadoop ecosystem as an open standard.

Key Milestones

  • 2013: Parquet project initiated
  • 2015: Parquet 1.0 released
  • 2016: Apache top-level project
  • 2018: Wide cloud platform adoption
  • 2020: Parquet 2.0 with improvements
  • Present: Industry standard for data lakes

Key Features

Core Capabilities

  • Columnar Storage: Column-oriented layout
  • Excellent Compression: 10-100x vs CSV
  • Column Pruning: Read only needed columns
  • Predicate Pushdown: Skip irrelevant data
  • Schema Evolution: Add columns over time
  • Nested Structures: Complex data types

Common Use Cases

Data Analytics

OLAP, business intelligence

Data Lakes

S3, Azure Data Lake

Machine Learning

Training data storage

Big Data

Spark, Hive, Presto

Advantages

  • Exceptional compression ratios
  • Fast analytical queries
  • Column-level operations
  • Storage cost savings
  • Wide ecosystem support
  • Schema evolution support
  • Cloud-native format

Disadvantages

  • Not human-readable
  • Slower for row-based operations
  • Write overhead for small updates
  • Requires specialized tools
  • Not ideal for transactional data
  • Learning curve

Technical Information

Format Specifications

Specification Details
File Extension .parquet
MIME Type application/vnd.apache.parquet
Format Type Columnar data
Compression Snappy, GZIP, LZO, Zstd
Schema Self-describing
License Apache 2.0

Common Tools

  • Processing: Apache Spark, Apache Hive, Presto
  • Cloud: AWS Athena, BigQuery, Snowflake
  • Python: PyArrow, Pandas, Dask
  • Viewers: parquet-tools, DBeaver