CSV to Parquet Converter Online
Convert CSV files to Apache Parquet format directly in your browser. Fast, private, and free — no upload to any server, no signup required.
- Upload a CSV file and convert to Parquet format instantly in your browser.
- 100% client-side — your data never leaves your device.
- No signup, no installation, no server upload required.
- Download optimized Parquet files ready for data pipelines and analytics.
- Supports large CSV files with efficient in-browser processing.
CSV to Parquet Converter Tool
All conversions happen in your browser, so your CSV data never leaves your device.
Why Use This CSV to Parquet Converter
Instant Browser-Based Conversion
Convert CSV to Parquet directly in your browser with no server round-trip. Your file is processed locally using WebAssembly for fast, efficient conversion without uploading data anywhere.
Columnar Storage Format
Parquet stores data in a columnar format that enables faster analytical queries and better compression. Converting CSV to Parquet can reduce file sizes by 50-90% while improving read performance.
Preserve Data Types
The converter automatically detects column types (strings, integers, floats, dates) from your CSV data and maps them to the appropriate Parquet data types for accurate, type-safe storage.
No Signup or Installation
Start converting CSV to Parquet immediately without creating an account or installing any software. Open the page, drop your file, and download the result.
100% Private and Secure
Your CSV data never leaves your device. All parsing and Parquet encoding happen locally in your browser, ensuring complete data privacy and security.
Optimized for Analytics
The generated Parquet files are compatible with Apache Spark, AWS Athena, Google BigQuery, DuckDB, Pandas, and other modern data tools. Perfect for preparing data for analytical workflows.
What Is the Parquet File Format?
Apache Parquet is an open-source columnar storage format designed for efficient data processing. Unlike row-based formats like CSV, Parquet stores data column by column, which enables better compression and faster queries when reading specific columns. Parquet is the standard file format for data lakes, big data pipelines, and cloud analytics platforms.
Converting CSV to Parquet is a common step in data engineering workflows. This free online converter lets you perform the conversion instantly in your browser without setting up Python, Spark, or any other tool.
Columnar Storage
Parquet organizes data by columns rather than rows. This means reading a single column from a multi-column dataset is extremely fast because only the relevant data is loaded from disk.
Efficient Compression
Because similar values are stored together in columns, Parquet achieves much better compression ratios than CSV. A 100MB CSV file can often compress to 10-30MB in Parquet format.
Schema and Type Safety
Parquet files embed their schema including column names, data types, and nullability. This eliminates parsing ambiguity and ensures data integrity across different tools and platforms.
Wide Tool Support
Parquet is supported by Apache Spark, Hadoop, AWS Athena, Google BigQuery, Snowflake, DuckDB, Pandas, Polars, and virtually every modern data processing framework.
How to Convert CSV to Parquet Online
- 1
Upload Your CSV File
Drag and drop a CSV file into the converter above, or click to select one from your computer. The file is read locally in your browser — nothing is uploaded to any server.
- 2
Review Your Data
The converter parses your CSV and displays a preview of the data with detected column types. Verify that columns and data types are correctly identified before converting.
- 3
Convert to Parquet
Click the convert button to transform your CSV data into Parquet format. The conversion uses efficient encoding and compression to produce an optimized Parquet file.
- 4
Download the Parquet File
Download the generated .parquet file to your computer. The file is ready to use with Spark, BigQuery, DuckDB, Pandas, or any other tool that supports the Parquet format.
CSV to Parquet Conversion Best Practices
Clean Your CSV First
Remove empty rows, fix inconsistent delimiters, and ensure headers are descriptive before converting. Clean input data produces better Parquet files with correct schema inference.
Use Consistent Data Types
Ensure each column contains a single data type. Mixing numbers and text in the same column will force the converter to treat the entire column as strings, reducing query performance.
Include a Header Row
Always include a header row with meaningful column names. These become the column names in the Parquet schema and are used by downstream tools to identify fields.
Handle Missing Values
Use empty cells or a consistent null marker for missing values. Parquet natively supports null values, so missing data is handled efficiently without placeholder strings.
Use UTF-8 Encoding
Ensure your CSV file uses UTF-8 encoding for maximum compatibility. Non-UTF-8 encoded files may produce garbled text or conversion errors in the Parquet output.
Check File Size Limits
Browser-based conversion works well for files up to several hundred megabytes. For very large datasets (multi-GB), consider using command-line tools like DuckDB or Apache Spark.
CSV to Parquet Converter FAQ
How do I convert a CSV file to Parquet online?
Upload your CSV file to the converter on this page. The tool reads the file in your browser, detects column types, and converts the data to Parquet format. Click download to save the .parquet file. No signup or server upload required.
Is my data safe when converting CSV to Parquet here?
Yes. This converter runs entirely in your browser. Your CSV file is never uploaded to any server — all parsing, type detection, and Parquet encoding happen locally on your device. Your data stays completely private.
What is the advantage of Parquet over CSV?
Parquet is a columnar format that offers much better compression (50-90% smaller files), faster analytical queries, built-in schema with data types, and native support for nested data. It is the standard format for modern data lakes and analytics platforms.
What tools can read Parquet files?
Parquet files can be read by Apache Spark, AWS Athena, Google BigQuery, Snowflake, DuckDB, Pandas (Python), Polars, Apache Arrow, and most modern data processing and analytics tools.
Does the converter preserve column types?
Yes. The converter automatically detects data types (strings, integers, floats, booleans, dates) from your CSV data and maps them to corresponding Parquet types. This ensures type-safe storage and correct behavior in downstream tools.
What is the maximum file size I can convert?
Since conversion happens in your browser, the limit depends on your device's available memory. Most modern computers can handle CSV files up to several hundred megabytes. For multi-gigabyte files, use command-line tools like DuckDB or pyarrow.
Can I convert Parquet back to CSV?
Yes. Use our free Parquet to CSV converter to convert Parquet files back to CSV format. Both conversions run entirely in your browser with the same privacy guarantees.
Is Parquet the same as Apache Arrow?
No. Parquet is a file storage format optimized for on-disk storage, while Apache Arrow is an in-memory columnar format optimized for computation. They are complementary — Arrow is often used to read and write Parquet files efficiently.
Need to view Parquet files? Try our Need to view Parquet files? Try our to explore Parquet data online.