Data Tools, Guides & Comparisons
One hub for everything in the data cluster. Clean and validate data, convert between formats, and process CSV, JSON, XML, Excel, and SQL — all with free browser-based tools that never upload your data to a server. Use the guides to understand which format to use, and the comparisons to make informed choices.
Overview
Choose what you need:
- Formatting JSON→JSON Formatter
- Comparing JSON files→JSON Diff
- Flattening JSON→JSON Flattener
- Converting JSON to CSV→JSON to CSV
- Cleaning CSV files→CSV Data Cleaner
- Merging CSV files→CSV Merger
- Splitting CSV files→CSV Splitter
- Validating XML→XML Validator
- Converting Excel to CSV→Excel to CSV Converter
Not sure which format to use? Read the pillar guide for a full decision framework.
Data Tools
All tools run locally in your browser — no data is uploaded or stored.
JSON Tools
Format, compare, flatten, and convert JSON data. Useful for inspecting API responses, debugging nested structures, and preparing data for downstream tools.
CSV Tools
Parse, filter, transform, clean, and convert CSV files without writing a script. All operations run in your browser on the raw text.
Excel Tools
Convert, merge, and clean Excel spreadsheets entirely in your browser using SheetJS — no file upload or server processing required.
XML & TSV Tools
Validate XML documents, query nodes with XPath, and convert between XML, TSV, and CSV formats.
SQL Tools
Format and prettify SQL queries for readability before committing to version control or sharing with your team.
Most data tools run locally in your browser. If a tool ever requires server-side processing, it will clearly say so on the tool page.
Data Guides
In-depth reference pages — start with the pillar guide, then explore by topic.
A practical guide to data formats for engineers — understand CSV, JSON, XML, and Excel, when to use each, and how to validate, convert, and transform data without writing a pipeline.
A practical guide to working with JSON data — how to validate, flatten, diff, convert, and move JSON between systems without writing a full pipeline.
JSON Schema is a vocabulary for defining structure and validation rules for JSON documents. Learn core keywords, practical validation workflows, and when to use JSON Schema in APIs, pipelines, and config files.
Data Comparisons
Decision-focused breakdowns to help you pick the right format or tool.
JSON is lightweight and maps to objects natively; XML adds namespaces, schemas, and document structure. Compare verbosity, validation, streaming, and real-world use cases to pick the right format.
CSV is simpler and better for tabular data; JSON handles nested structures and is the standard for APIs. Compare verbosity, schema support, tooling, and real-world use cases.
CSV is plain text and universally portable; Excel (.xlsx) adds data types, formatting, multiple sheets, and formulas. Compare file size, automation compatibility, and use cases for analytics, pipelines, and human editing.
Frequently Asked Questions
What's the difference between CSV and JSON?
CSV is a plain-text tabular format — rows and columns separated by commas. It is compact, universally supported, and ideal for flat data. JSON supports nested objects and arrays, which CSV cannot represent natively. Use CSV for tabular data destined for spreadsheets, databases, or data pipelines. Use JSON for nested data, API payloads, and configuration files.
When should I use JSON instead of XML?
JSON is the default choice for web APIs and config files — it is lighter, maps directly to objects in every major language, and is easier to read. XML is better when you need document-centric data with mixed content (text interspersed with markup), namespace support, or strict schema validation via XSD. For new projects without legacy constraints, JSON is almost always the right choice.
Can I clean CSV files in my browser?
Yes. The CSV Data Cleaner tool runs entirely in your browser — no data is uploaded to any server. You can remove empty rows, trim whitespace, normalize line endings, deduplicate rows, and replace null/NA values. All processing happens locally, making it safe for production data and files containing sensitive information.
Is Excel better than CSV for data pipelines?
No — CSV is almost always better for automated pipelines. CSV is plain text, parseable by any language without a library, and works consistently across tools. Excel adds formatting, data types, and multiple sheets, but those features make automation fragile: formulas can silently break, number formats vary by locale, and date handling is notoriously inconsistent. Use CSV for pipelines and Excel for human-readable reporting.
What does JSON Schema do?
JSON Schema is a vocabulary for defining the expected structure and validation rules for a JSON document. It lets you specify required fields, data types, value ranges, pattern constraints, and nested object shapes. Use it to validate API request bodies, enforce config file structure, or document your data contracts. See the JSON Schema Explained guide for a full walkthrough.
Can I convert between these formats safely?
Yes, with caveats. CSV to JSON is lossless for flat tabular data. JSON to CSV requires flattening if the JSON contains nested objects — use the JSON Flattener before exporting. Excel to CSV may lose formulas (only cell values are preserved) and date formatting can vary. XML to JSON loses XML-specific features like attributes, namespaces, and processing instructions. All conversion tools on this page clearly describe any data loss in their documentation.
Which data tool should I start with?
Start with the Data Formatting & Processing Basics guide if you need to understand which format to use and why. If you already know your format, go directly to the relevant tool: JSON Formatter for inspecting JSON, CSV Data Cleaner for cleaning CSV, or Excel to CSV Converter for spreadsheet conversion. Each tool page includes how-to instructions and common use cases.
Where to go next
Start with the complete guide, or jump straight to the tools.