Cursor's Bloated Storage vs. Claude Code's Clean Architecture
A deep dive into Cursor's complex 8GB local storage reveals why Claude Code's simple JSONL-based approach is better for developers in terms of tooling, privacy, and performance.
Why it matters
The article's insights into Cursor's storage complexity versus Claude Code's clean architecture can help developers make informed choices about their AI assistant tools and workflows.
Key Points
- 1Cursor's local storage is spread across multiple locations and includes chat databases, transcript files, and a large global state database
- 2Claude Code takes a simpler approach, storing each project's complete session transcript in a single JSONL file
- 3Claude Code's storage structure enables easier session review, cleanup scripts, and integration with other tools
Details
The article examines a developer's analysis of Cursor's local storage, which revealed a sprawling 8GB footprint across various locations, including SQLite databases, transcript files, and a large global state database. In contrast, Claude Code's approach is to store each project's complete session transcript in a single JSONL file within the ~/.claude/projects directory. This simpler storage structure offers several advantages for developers, such as easier tooling integration, better privacy controls, and more efficient performance compared to Cursor's complex database-driven approach. The article highlights how Claude Code's storage philosophy aligns with Anthropic's focus on transparency and simplicity, providing developers with more control over their data.
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