viewparquet
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SQL editor · S3 & URL · optional AI · private by default

Private online Parquet viewer & SQL workbench in your browser.

Explore Parquet at the speed of thought: open files from disk, S3, or a URL, run DuckDB SQL, and scan millions of rows without uploading anything. Free, no install, no account. Optional AI with your own key.

Parquet & GeoParquet first · CSV, JSON also supported

See what it does
One private path from file to answer
Live product model
viewparquet engineDuckDB · WebAssembly
trips_nyc_2024.parquet28,431,902 rows · 42 columns
Ready
Your dataset never passes through viewparquet servers.
The actual workbenchLocal data · full DuckDB SQL · no install
trips_nyc_2024.parquet
Query 1fares_by_type
SELECT payment_type,
AVG(fare_amount) AS avg_fare
FROM 'trips_nyc_2024.parquet'
GROUP BY 1 ORDER BY 2 DESC;
trip_id
pickup_time
fare_amount ▲
payment_type
1
t_8f3a21
2024-03-14 08:12:04
24.50
card
2
t_8f3a22
2024-03-14 08:12:11
18.75
card
3
t_8f3a23
2024-03-14 08:12:18
42.20
cash
4
t_8f3a24
2024-03-14 08:12:25
9.80
card
5
t_8f3a25
2024-03-14 08:12:31
56.30
card
6
t_8f3a26
2024-03-14 08:12:38
31.00
card
28,431,902 rows

Built for data teams that live in columnar files

Local
files never upload to viewparquet
Stream
Parquet from S3 & URLs
WASM
DuckDB running in your tab
AI
bring your own key

Parquet guides

Start with the task you need to finish

Direct, practical guides for opening, inspecting, converting, and querying Parquet files.

Open & view

Open a Parquet file online

View rows, schema, metadata, and compression without Python or an install.

Convert

Parquet to CSV

Filter the rows and columns you need, then export a spreadsheet-friendly CSV.

Convert

Parquet to JSON

Preserve nested structs and lists in a local JSON Lines export.

Excel

Open Parquet in Excel

Choose the quickest route through CSV export or Microsoft Power Query.

Cloud

Query Parquet on S3

Read public, presigned, or private objects directly from your browser.

Spatial

View GeoParquet

Inspect geometry columns, GeoParquet metadata, attributes, and SQL results.

Need a quick answer? Browse the Parquet FAQ.

S3 & URL

Query cloud Parquet without uploading it

Point viewparquet at a public HTTPS link, presigned URL, or s3:// object, or connect a private bucket with keys that stay in your browser. DuckDB streams only the byte ranges it needs, so large remote Parquet stays fast. Works with AWS S3, Cloudflare R2, Google Cloud Storage, and MinIO.

Read the S3 guide
trips_nyc_2024.parquet
Open from S3 / URL
URLCredentials
Object URL
s3://analytics-prod/events/2024/trips.parquet
Amazon S3Cloudflare R2GCSMinIO

DuckDB streams byte ranges from the bucket — credentials sign requests in-browser and are never sent to viewparquet.

SQL editor

Real SQL, right in the browser

Write full DuckDB SQL with multi-tab queries, schema autocomplete, and one-click execution. Joins, CTEs, and window functions, then export results to Parquet, CSV, or JSON.

trips_nyc_2024.parquet
Query 1fares_by_type
WITH by_type AS (
SELECT payment_type, AVG(fare_amount) AS avg_fare,
COUNT(*) AS trips
FROM 'trips_nyc_2024.parquet'
GROUP BY 1
)
SELECT * FROM by_type ORDER BY avg_fare DESC;
payment_type
avg_fare
trips
card
34.18
21,902,114
cash
27.55
6,201,338
no charge
0.00
328,450
3 rows

Results grid

Scan millions of rows without the wait

A virtualized grid scrolls huge result sets smoothly, with type-aware coloring and per-column stats: cardinality, ranges, and null counts at a glance.

trips_nyc_2024.parquet
trip_id
pickup_time
fare_amount ▲
payment_type
1
t_8f3a21
2024-03-14 08:12:04
24.50
card
2
t_8f3a22
2024-03-14 08:12:11
18.75
card
3
t_8f3a23
2024-03-14 08:12:18
42.20
cash
4
t_8f3a24
2024-03-14 08:12:25
9.80
card
5
t_8f3a25
2024-03-14 08:12:31
56.30
card
6
t_8f3a26
2024-03-14 08:12:38
31.00
card
7
t_8f3a27
2024-03-14 08:12:44
12.40
cash
8
t_8f3a28
2024-03-14 08:12:50
88.10
card
28,431,902 rows

AI assistant

Ask in plain language, get SQL back

Describe what you need and the assistant drafts queries, explains your schema, and fixes errors, grounded in the file you have open. Bring your own OpenRouter key and control what context is shared in Settings → AI.

trips_nyc_2024.parquet
trip_id
pickup_time
fare_amount ▲
payment_type
1
t_8f3a21
2024-03-14 08:12:04
24.50
card
2
t_8f3a22
2024-03-14 08:12:11
18.75
card
3
t_8f3a23
2024-03-14 08:12:18
42.20
cash
4
t_8f3a24
2024-03-14 08:12:25
9.80
card
28,431,902 rows
Chat 1+

You

What is the average fare by payment type?

Assistant

Here is a grouped query on your open file:

SELECT payment_type,
  AVG(fare_amount) AS avg_fare
FROM 'trips_nyc_2024.parquet'
GROUP BY 1;
Ask anything about your data…

Private by default

Your data stays under your control

Processing runs in your browser with DuckDB-WASM. Datasets never upload to viewparquet. Open from disk, S3, or a URL with keys that stay local. Optional AI is explicit and BYOK goes browser-to-provider.

trips_nyc_2024.parquet
NetworkXHR/Fetch
NameSource
trips_nyc_2024.parquetdisk · local
s3://analytics/events.parquetstream · direct
duckdb-eh.wasmcache
openrouter.ai/api/v1/…optional · AI
No uploads to viewparquet — S3 & AI are direct from your browser
Open from S3 or a URL
Live

Formats

Parquet-first, GeoParquet-ready.

Purpose-built for columnar files, with CSV and JSON supported when you need them, all processed locally in DuckDB-WASM.

  • Parquet.parquet

    Native columnar

    First-class
  • GeoParquet.geoparquet

    With geometry

    First-class
  • CSV.csv

    Auto-detected schema

    Supported
  • TSV.tsv

    Tab-delimited

    Supported
  • JSON.json

    Objects or arrays

    Supported
  • JSON Lines.jsonl

    One record per line

    Supported

FAQ

Questions, anticipated.

Got questions? Here are the most common ones about viewparquet.

Do my files leave the browser?

Your datasets are processed locally with DuckDB WASM and never upload to viewparquet. Remote reads go directly from your browser to the bucket or URL. Optional AI sends only the context you allow, directly from your browser to your configured BYOK provider.

Can I run SQL on my data?

Yes. The SQL editor supports full DuckDB syntax with multi-tab queries, schema autocomplete, and exports. The AI assistant can draft queries, explain schema, and fix errors, grounded in the file you have open.

How does the AI assistant work?

Add your own OpenRouter/provider key for BYOK mode. Use data-sharing presets to control whether column names, types, metadata, or sample values are included.

What file types are supported?

Parquet and GeoParquet are first-class formats for the fastest path. CSV, TSV, JSON, and JSON Lines are also supported as secondary formats.

Is there a file size limit?

File size is only limited by your browser's available memory. The viewer streams and paginates for efficiency.

Can I open files from S3 or a URL?

Yes. Open data from a public HTTPS or presigned URL, a public s3:// object, or a private bucket using in-browser access keys (or temporary STS tokens), plus S3-compatible stores like Cloudflare R2, Google Cloud Storage, and MinIO. DuckDB streams only the bytes it needs; credentials stay in your browser and never pass through viewparquet servers.

Working with Parquet files? See the full Parquet FAQ : how to open, view, query, and convert Parquet.

Changelog

See what's new in viewparquet
2.5

Copy cells and keep your column layout

2.4

BYOK AI assistant for private data work

2.3

Open Parquet from S3 & URLs — privately

2.2

AI assistant with bring-your-own-key privacy

Learn & Explore

Latest Blog Posts

AI data pipelines, Parquet for LLM workloads, DuckDB, and columnar analytics.

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