Parquet Viewer Online - Free In-Browser Parquet File Reader & SQL Explorer
View, inspect, and query Apache Parquet files online instantly in your browser. 100% private local processing using WebAssembly. View schemas, metadata, and export to CSV or JSON.
Drag and drop your .parquet file here
Supports local Apache Parquet binary files (.parquet) up to browser memory limits.
sample_analytics.parquet
24.0 KB • 8 Rows • 8 Columns • Codec: SNAPPY
| # | id(INT64) | name(STRING) | email(STRING) | age(INT32) | country(STRING) | active(BOOLEAN) | salary(DOUBLE) | created_at(TIMESTAMP) |
|---|---|---|---|---|---|---|---|---|
| 1 | 1001 | Alice Smith | alice@example.com | 28 | United States | true | 92000.5 | 2024-01-15T08:30:00Z |
| 2 | 1002 | Bob Jones | bob@example.com | 35 | United Kingdom | true | 85500 | 2024-01-16T10:15:00Z |
| 3 | 1003 | Charlie Chen | charlie@example.com | 42 | Canada | false | 110000 | 2024-01-18T14:45:00Z |
| 4 | 1004 | Diana Prince | diana@example.com | 31 | Germany | true | 98000.75 | 2024-01-20T09:00:00Z |
| 5 | 1005 | Evan Wright | evan@example.com | 24 | United States | true | 65000 | 2024-01-22T11:20:00Z |
| 6 | 1006 | Fiona Gallagher | null | 29 | Ireland | false | 74000 | 2024-01-25T16:00:00Z |
| 7 | 1007 | George Clark | george@example.com | 48 | Australia | true | 125000 | 2024-01-28T13:10:00Z |
| 8 | 1008 | Hannah Abbott | hannah@example.com | 37 | United Kingdom | true | 91000.25 | 2024-02-01T07:50:00Z |
How to Use
Online Parquet Viewer & Data Explorer Overview
The ToolMono Online Parquet Viewer & Data Explorer is a browser-native workspace for data engineers, analytics engineers, and data practitioners to open, inspect, search, and query Apache Parquet files online without installing Python, Pandas, or PyArrow.
Processes binary Parquet magic headers, row groups, physical types, and logical types locally inside browser memory.
Processed locally in your browser. Your Parquet dataset is never uploaded to ToolMono servers or external APIs.
Write and execute SQL queries (SELECT * FROM parquet_file WHERE ...) and export query results to CSV or JSON.
How to View and Read Parquet Files Online
- Load Your File: Drag and drop a
.parquetfile onto the dropzone or click Try Sample Dataset to explore immediately. - Explore Table Rows: In the Data tab, search values, sort columns, or scroll through dataset rows with type-aware formatting.
- Inspect Schema & Types: Click the Schema tab to view column physical types (INT64, DOUBLE, BYTE_ARRAY), logical types (UTF8, TIMESTAMP), and nullability.
- Inspect Metadata: Click the Metadata tab to review compression codecs (SNAPPY, ZSTD, GZIP), row count, file size, and generator version.
- Run In-Browser SQL Queries: Switch to the SQL tab to write custom SELECT queries and export filtered results to CSV or JSON.
Client-Side Parquet Processing with WebAssembly
Traditional web converters require uploading large datasets to cloud servers. ToolMono utilizes browser WebAssembly memory buffers to read binary Parquet metadata headers and data pages locally. This enables instant viewing of multi-megabyte Parquet files while guaranteeing zero data leakage.
Parquet Schema and Metadata Inspection
Parquet Metadata Breakdown
- File Summary: File size, total row count, column count, row group count, format version, and creator string.
- Physical vs Logical Types: Differentiates raw binary storage (e.g.
INT64) from logical semantics (TIMESTAMP_MILLIS,DECIMAL). - Compression Codecs: Detects SNAPPY, ZSTD, GZIP, and UNCOMPRESSED row group column chunk compression.
Query Parquet Files with SQL
Filter and aggregate Parquet rows using standard SQL queries in the integrated SQL Editor tab:
-- Select active users with salary over $80,000 SELECT name, email, salary, country FROM parquet_file WHERE active = true AND salary > 80000; -- Aggregate user count by country SELECT country, COUNT(*) as total_users FROM parquet_file GROUP BY country;
Why Use Parquet Instead of CSV?
Apache Parquet (.parquet)
- Columnar binary format optimized for analytical queries
- Built-in typed schemas (INT64, TIMESTAMP, DECIMAL)
- High-ratio compression (SNAPPY, ZSTD)
- Reads selected columns without scanning full files
Comma-Separated Values (.csv)
- Row-oriented plain text format
- Lacks explicit data type definitions
- Uncompressed files require significantly more disk space
- Requires scanning entire file for single column reads
How to Open a Parquet File Without Python
Developers frequently install heavy Python packages (pip install pandas pyarrow duckdb) just to view the columns or rows of a .parquet file. ToolMono provides an instant browser-native viewer that opens Parquet files without installing local runtime environments.
100% Client-Side Privacy Statement
100% Client-Side Privacy Statement
Processed locally in your browser. Your Parquet dataset, customer records, and financial data are not uploaded to ToolMono servers or external cloud storage.
Frequently Asked Questions
References & Standards
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