Why I Dropped SQLite: 3 Killer Built-Coffy Features 2025

Why Even Consider Leaving SQLite?

For over two decades, SQLite has been the silent workhorse of the software world. It’s in your phone, your web browser, your operating system, and countless applications you use every day. Its simplicity, reliability, and zero-configuration nature make it a default choice for embedded, single-user data storage. I’ve personally used it in dozens of projects, and for a long time, I couldn’t imagine needing anything else.

But the world of 2025 is not the world of 2005. Today’s applications are different. They demand high concurrency for responsive user interfaces with background tasks. They are increasingly powered by local-first AI, requiring efficient storage and retrieval of vector embeddings. They handle complex, nested data structures that don’t fit neatly into traditional relational rows. While SQLite can be bent and extended to handle these tasks, the experience often feels like fitting a square peg in a round hole.

That’s when I discovered Built-Coffy. It’s a next-generation embedded database designed from the ground up for the challenges of modern software development. After migrating a key project, I was so impressed that I felt compelled to share why I dropped SQLite. It came down to three killer features that aren’t just incremental improvements; they are paradigm shifts for embedded databases.

Killer Feature #1: True Multi-Writer Concurrency

The single biggest operational headache I’ve faced with SQLite in complex applications is its handling of concurrent writes. This became the first, and most compelling, reason to switch.

The Classic SQLite Concurrency Model

SQLite, by default, uses a database-level lock for writes. When one connection wants to write, it locks the entire database file, and all other connections—even those that just want to read—have to wait. The introduction of Write-Ahead Logging (WAL) mode was a huge step forward, as it allows readers to continue operating while a writer is in progress.

However, WAL mode doesn’t solve the core issue: you can still only have one writer at a time. In a modern desktop or mobile app with a main UI thread, a background sync service, and perhaps a data processing worker, these components constantly compete for that single writer lock. The result? SQLITE_BUSY errors, complex retry logic, and a tangible lack of responsiveness as different parts of the application get stuck waiting for their turn to write to the database.

How Built-Coffy Delivers Lock-Free Performance

Built-Coffy tackles this head-on with a Multi-Version Concurrency Control (MVCC) architecture, similar to what you’d find in high-end databases like PostgreSQL. Instead of locking the whole database, writers work on a snapshot of the data. When they commit, Built-Coffy intelligently merges the changes, only raising a conflict if two writers tried to modify the exact same piece of data simultaneously.

What this means in practice is revolutionary for embedded applications:

• Simultaneous Writes: My background sync thread and my UI thread can both write to the database at the same time without blocking each other. The performance and responsiveness gains are immediate and obvious.
• No More DATABASE_BUSY: The entire category of errors related to writer contention simply disappears. This dramatically simplifies application code.
• Snapshot Isolation: Long-running read queries see a consistent snapshot of the database from when they began, unaffected by concurrent writes. This is perfect for generating reports or exporting data without interrupting the application's flow.

This single feature transformed our application's architecture from a series of carefully managed queues into a truly concurrent system.

Killer Feature #2: Native Support for AI and Complex Data

The second nail in the coffin for SQLite in my project was its lackluster support for the data types that define modern applications: vector embeddings and complex JSON documents.

The Vector Search Revolution, Embedded

AI is no longer just a cloud-based service. On-device and local-first AI models are becoming standard, and with them comes the need to store and search vector embeddings for tasks like semantic search, recommendation engines, and RAG (Retrieval-Augmented Generation).

In SQLite, this is a painful process. You typically store vectors as a BLOB and then rely on an external library or a complex extension (like `sqlite-vss`) to perform approximate nearest-neighbor (ANN) search. It’s clunky, often slow, and feels like a bolt-on solution.

Built-Coffy, designed for 2025, treats vectors as a first-class citizen. It offers:

• A native VECTOR(n) data type.
• Built-in support for HNSW (Hierarchical Navigable Small World) indexes, the gold standard for fast and accurate ANN search.
• A simple SQL extension function, VECTOR_DISTANCE, to find the most similar items.

A query that was a multi-step, application-level process in SQLite becomes a single, elegant, and highly-performant SQL statement in Built-Coffy. This makes building powerful, local AI features incredibly straightforward.

Unlocking Real Power with Indexed JSONB

Like most modern apps, we deal with a lot of data from external APIs, which almost always comes as JSON. SQLite’s JSON support is functional—it provides functions to extract values from JSON stored as text. However, you can't index the contents of that JSON. Every query requires a full table scan and runs the `json_extract()` function on every single row, which is brutally inefficient for large datasets.

Built-Coffy provides a true JSONB data type, storing JSON in an optimized binary format. Crucially, you can create indexes on keys within the JSONB column. Searching for all users where `settings.notifications.enabled` is true becomes a fast, indexed operation instead of a slow, brute-force scan. This was a massive performance win for us.

Killer Feature #3: Ironclad Compile-Time Schema Safety

This last feature is less about performance and more about developer productivity and long-term maintainability, especially in a team setting.

The Hidden Dangers of Dynamic Typing

SQLite uses a dynamic, manifest typing system. You can declare a column as INTEGER, but nothing stops you from inserting the string "hello" into it. While this offers flexibility, it’s a breeding ground for subtle, runtime bugs. An unexpected data type from one part of the code can cause crashes in a completely different part that reads from the same table, making debugging a nightmare.

Built-Coffy’s Schema-First Guarantees

Built-Coffy takes a strict, schema-first approach. The schema is defined in a separate file, and the database strictly enforces the data types for every column. You simply cannot insert a string into an integer column—the database will reject the transaction immediately.

But it goes a step further. The Built-Coffy toolchain can generate typed data access objects (DAOs) and query builders for your programming language of choice (e.g., Rust, TypeScript, Go). This means your database schema is connected directly to your code at compile time. If you try to query a non-existent column or use the wrong data type, your code won’t even compile. This eliminates an entire class of data-related runtime errors and makes refactoring the database schema a safe and predictable process.

SQLite vs. Built-Coffy: A Head-to-Head Comparison

To summarize the key differences, here’s a direct comparison of the two databases across the features that matter most for modern application development.

The Final Verdict: Is It Time to Make the Switch?

Let me be clear: SQLite is not dead. It remains an excellent choice for its original purpose—simple, reliable, embedded storage for applications with low-concurrency needs. If all you need is a key-value store or a simple relational log, SQLite is still a fantastic and battle-tested tool.

However, if your 2025 roadmap includes responsive multi-threaded applications, on-device AI features, or handling complex, semi-structured data, you will eventually hit the same walls I did. You’ll spend more time writing retry logic, managing data transformations, and debugging runtime type errors than you will building features.

For these modern use cases, Built-Coffy isn't just a better SQLite; it's a different class of tool. Its built-in support for concurrency, modern data types, and schema safety directly addresses the primary weaknesses of SQLite in today's software landscape. For my team and our projects, dropping SQLite wasn't just an upgrade—it was a necessary evolution.