Terminal-Based TUI

Deep Inspection for Parquet Files & Apache Iceberg Tables

A powerful forensics tool for analyzing file structure, metadata, row groups, column statistics, and table evolution with an intuitive terminal interface.

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Parquet Analysis
Iceberg Tables
S3 & Local Files
Performance Testing

Why Data Engineers Use TableSleuth

Direct visibility into the file-level details that determine your data lakehouse performance

Troubleshoot Without Guesswork

  • See actual row group sizes and distribution patterns
  • Identify small file problems before they impact query performance
  • Understand compression effectiveness at the column level
  • Compare snapshot performance characteristics side-by-side
  • Diagnose why queries are scanning more data than expected

Data Quality Forensics

  • Inspect column statistics (min/max, null counts) without running queries
  • Verify partition pruning is working by examining manifest files
  • Catch schema evolution issues before they break pipelines
  • Profile data distributions to understand skew and cardinality
  • Validate that delete files (MOR) are being applied correctly

Cost Optimization Intelligence

  • Identify bloated partitions consuming excessive storage
  • Find opportunities for file compaction
  • Understand which columns are driving storage costs
  • Evaluate compression strategy effectiveness
  • Spot redundant data that can be cleaned up

Operational Confidence

  • Verify table maintenance operations (compaction, expiration) are working
  • Understand the impact of schema changes before applying them
  • Debug catalog synchronization issues
  • Validate S3 Tables and Glue Catalog configurations
  • Inspect snapshot lineage and table evolution history

Development Velocity

  • No need to write exploratory queries to understand file structure
  • Instant feedback on data layout decisions
  • Quick validation of partitioning strategies
  • Fast iteration on table optimization approaches
  • Terminal-based workflow that fits into existing dev environments

Key Features

Parquet Analysis

  • File structure & metadata inspection
  • Row group analysis with statistics
  • Column-level profiling
  • Data sample preview
  • Compression & encoding details

Iceberg Table Analysis

  • Snapshot history & evolution
  • Manifest file inspection
  • Delete file (MOR) forensics
  • Snapshot comparison
  • Performance benchmarking

Cloud Integration

  • S3 file access
  • AWS Glue Catalog support
  • S3 Tables integration
  • PyIceberg catalog support
  • Local & remote files

Performance Testing

  • Query performance comparison
  • Snapshot benchmark testing
  • GizmoSQL integration
  • DuckDB profiling
  • Arrow Flight SQL support

See It In Action

Parquet File Inspection

Parquet Structure

File Structure & Schema

Row Groups

Row Group Analysis

Data Sample

Data Sample View

Profile

Column Profiling

Iceberg Table Analysis

Iceberg Overview

Snapshot Overview

Performance

Performance Testing

Deletes

Delete Files (MOR)

Compare

Snapshot Comparison

Quick Start

Installation

pip install tablesleuth

Requires Python 3.13+ and uv

Basic Usage

Inspect a Parquet File

tablesleuth inspect /path/to/file.parquet

Inspect S3 Files

tablesleuth inspect s3://bucket/path/to/file.parquet

Analyze Iceberg Table

tablesleuth iceberg --catalog glue --namespace db --table my_table

Documentation

Setup Guide

Complete installation and configuration instructions

User Guide

Comprehensive guide to all features and workflows

Architecture

Technical architecture and design documentation

GizmoSQL Setup

Deploy GizmoSQL for advanced profiling features

Development

Contributing and development environment setup

Developer Guide

API reference and extension development

Ready to Start Investigating?

Install TableSleuth and start analyzing your Parquet files and Iceberg tables today.

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