Transform your data in seconds

The JSON format (JavaScript Object Notation) has become the de facto standard for data exchange in modern web applications and APIs. However, many professionals need to convert this data to CSV (Comma-Separated Values) to analyze it in spreadsheets such as Microsoft Excel, Google Sheets or LibreOffice Calc. This is where our online JSON to CSV converter makes the difference.

DataSwift intelligently analyzes your JSON structure, flattening nested objects and expanding arrays to produce a perfectly formatted CSV file. Unlike other online tools, our converter correctly handles complex data types: nested objects, mixed object arrays, null values and optional fields. The result is a clean table ready to import into any analysis software.

Common use cases include: exporting REST API data for later analysis, migrating data between systems that use different formats, preparing datasets for Business Intelligence tools like Tableau or Power BI, and creating reports from third-party API responses. With DataSwift, all this happens in seconds, directly in your browser, with no software installation and no data sent to any external server.

Our converter supports large JSON files with automatic encoding detection and full Unicode character support. You can paste your JSON directly into the editor. The result downloads instantly as a .csv file, ready to open in your favorite tool.

Working with complex SQL queries can quickly become frustrating when code is poorly indented, subqueries are crammed into a single line and aliases are hard to follow. Our online SQL formatter solves this instantly, transforming any messy query into clean, readable and well-structured SQL code.

DataSwift's SQL formatter supports the major database dialects: MySQL, PostgreSQL, SQLite, Microsoft SQL Server and Oracle. It automatically recognizes window functions, CTEs (Common Table Expressions), correlated subqueries, nested CASE statements and complex JOIN clauses. Every element is indented and aligned following industry-accepted SQL style best practices.

This tool is especially useful for development teams that need to maintain a consistent code style across their repositories. Backend developers, DBAs and data analysts can use it to review queries before committing, document stored procedures, optimize production queries or simply understand a query inherited from a colleague.

In addition to formatting, our beautifier offers real-time syntax highlighting, making it easy to visually identify keywords, table names, aliases and functions. You can copy the formatted result with a single click or download it as a .sql file to include in your project.

Converting CSV to JSON is a fundamental task in modern web development. APIs expect JSON, frontend apps consume JSON, and JavaScript and TypeScript frameworks work natively with JSON objects. However, many data sources still use the CSV format. Our online CSV to JSON converter bridges this gap quickly and efficiently.

DataSwift automatically detects your CSV delimiter (comma, semicolon, tab or pipe), infers the data type of each column (numbers, booleans, dates and strings) and generates a clean, valid JSON. Unlike basic tools that treat everything as text, our converter produces correctly typed data, saving time in subsequent processing steps.

This tool is perfect for developers who need to import spreadsheet data into web apps, for data scientists preparing datasets for Python or R analysis, and for data engineers building ETL pipelines. All processing happens in your browser, ensuring maximum privacy and speed.

Every software project needs test data at some stage. Whether it is populating a development database, creating convincing demos for clients, running load tests or generating fixtures for automated tests, having realistic fake data is essential. Our online fake data generator lets you create exactly the data you need in seconds.

You can define the exact structure of your data with a custom schema. For example, you can create a dataset of 1000 users with name, email, age, country and registration date, and export it directly as a JSON array ready to insert into your app, or as SQL INSERT statements compatible with your database.

This tool is indispensable for QA teams who need diverse data for testing, for frontend developers who want to fill interfaces with realistic content, for instructors preparing teaching material with example datasets, and for startups who need convincing demos without using real user data. Everything is generated in your browser, no internet connection required.

Regular expressions (regex) are one of the most powerful — and most intimidating — tools for developers. Writing a correct regex to validate an email, extract data from complex text or clean a dataset can be a long trial-and-error process. Our online regex tester radically simplifies this by providing instant visual feedback as you write your expression.

DataSwift's tester highlights matches in real time directly on the test text, and shows each captured group in a side panel along with the position (index) of each match in the original text. It supports all standard JavaScript regex flags: global (g), case insensitive (i), multiline (m), dotall (s), unicode (u) and sticky (y).

Typical use cases include: validating input data formats (emails, phones, postal codes, URLs), extracting information from server logs, cleaning and transforming text for data processing, web scraping and HTML parsing, and migrating data between formats.

Base64 is an encoding scheme that converts binary data into a text representation using 64 printable ASCII characters. It is widely used in web development to embed images in CSS and HTML (data URIs), transmit binary data over text-based protocols like HTTP and SMTP, store JWT authentication tokens, and encode email attachments. Our online Base64 encoder and decoder makes working with this format fast and intuitive.

With DataSwift you can encode and decode both plain text and binary files. For text, simply paste or type your content and you will get the Base64-encoded version instantly. For files (images, PDFs, documents), drag the file to the upload area and the tool will generate the corresponding Base64 string ready to copy into your code as a data URI or send through an API.

Our tool supports both standard Base64 and URL-safe Base64 (which replaces + and / with - and _, and removes the = padding), which is common in URLs, filenames and authentication tokens. Decoding works the same way: paste a Base64 string and the tool will automatically detect whether the original content is readable text or a binary file.

One of the most common challenges for developers and data analysts is working with real production data locally without violating GDPR, CCPA or other data privacy regulations. You cannot use a CSV full of real customer emails, phone numbers or credit card numbers on your local machine. Our GDPR Data Masker solves this problem in seconds.

Simply paste your CSV with real data and DataSwift automatically detects which columns contain sensitive information — emails, names, phone numbers, UUIDs, card numbers and more — and replaces them with realistic fake data while keeping all other columns intact. You can override the detection for any column and choose exactly what masking rule to apply.

Because all processing happens in your browser, your sensitive data never leaves your computer. This is the safest possible way to anonymize data for development, testing and demos. The output CSV is ready to use in any environment with zero privacy risk.

Messy text is a universal pain point. Exported data from databases, copied content from PDFs, or outputs from legacy systems often come with trailing spaces, inconsistent line endings, duplicate rows, leading numbers or random special characters. Our Data Cleaner fixes all of these issues with a single click.

Paste your text and toggle the cleaning operations you need: trim whitespace, collapse multiple spaces, remove blank lines, remove duplicate lines (case-insensitive), convert to lowercase or uppercase, strip special characters, remove leading list numbers, sort lines alphabetically, or normalize line endings. Each toggle takes effect instantly, so you can see the result in real time as you experiment.

The tool displays live statistics showing the number of input vs output lines and characters, and how many lines were removed. This is particularly useful when cleaning large datasets, log files or exported lists where duplicates and formatting issues are hard to spot manually.