# Local First Architecture for Frontends

Source: https://www.egnworks.com/blog/local-first-architecture-frontend  
Author: Jacob Val  
Published: 2026-08-30  
Updated: 2026-08-30  
Category: Frontend Architecture  
Tags: Local First, Data Sync

> An in depth guide to local first architecture for frontend teams. Covers CRDTs, sync engines, offline support, and how tools such as Automerge, Yjs, ElectricSQL, and PowerSync let applications treat the device as the primary source of truth.

---

## Introduction

The traditional client server model treats the server as the single source of truth. Every meaningful interaction, saving a document, adding an item to a cart, sending a message, waits on a round trip to that server before the interface can confidently update. When the network is slow or unavailable, the application either freezes, shows a spinner, or stops working entirely.

Local first architecture inverts that relationship. The device holds a complete, primary copy of the user's data. Reads and writes happen instantly against that local copy, and changes are synchronized to a server or to other devices in the background whenever a connection is available. The cloud becomes a layer for backup and coordination between devices rather than the authority the application depends on to function.

The term was introduced in 2019 by the research lab Ink and Switch, in an essay authored by Martin Kleppmann along with several collaborators, describing a set of ideals for software that gives users both real time collaboration and full ownership of their own data. Interest in the approach has grown steadily since, and by 2026 it has moved well beyond research prototypes. Products used by millions, including Linear and Figma, have demonstrated that local first principles can scale to production, and the surrounding tooling, from CRDT libraries to purpose built sync engines, has matured to the point where teams no longer need deep distributed systems expertise just to get started.

## What Local First Architecture Means

A local first application keeps a full copy of its data on the user's device. Reads and writes are applied to that local copy first, which is why interactions feel instant even on a poor connection. Changes are then queued and synchronized to a server or to other devices whenever connectivity allows.

It helps to place this alongside two other common models.

The server authoritative model is the traditional approach, where every write requires a confirmed response from the server before the interface can safely reflect the change. The optimistic UI model is a middle ground, where the client updates immediately for a responsive feel but still treats the server's response as final, quietly rolling back the change if the server rejects it.

Local first goes a step further than either. The local copy simply is the truth for that device. Conflicts between devices are resolved automatically by data structures designed for merging, rather than by a central server deciding which write wins.

## The Role of CRDTs

A Conflict Free Replicated Data Type, usually shortened to CRDT, is a data structure built so that when two devices independently edit the same piece of data, both sets of changes can be merged automatically into a consistent result. No coordinating server is required during the edit, and no user has to manually resolve a conflict after the fact.

Two implementations dominate the current ecosystem. Automerge, which originated at Ink and Switch, targets JSON shaped documents and history rich applications, and its more recent versions moved core operations into a Rust implementation, cutting memory use dramatically and making large documents practical to work with directly inside a browser. Yjs is the more common choice for real time text editors, powering collaborative editing in tools such as Tiptap and BlockNote, and is generally favored when the primary use case is rich text rather than general purpose document state.

## Sync Engines and How They Work

A CRDT solves how changes merge. A sync engine solves how those changes travel between a device and a server, and between devices themselves. Most sync engines pair a local database, frequently SQLite running directly on the device, with a background process that tracks which changes have already been sent, requests changes that happened elsewhere, and applies them to the local copy without disrupting whatever the user is currently doing.

The ecosystem around this idea has grown considerably. ElectricSQL streams data from a Postgres database directly to local clients. PowerSync keeps an on device SQLite database synchronized with a Postgres backend. Tools such as Replicache, TanStack DB, LiveStore, Triplit, and Zero each take a slightly different position on where the sync boundary sits, whether that is replicating database rows, document operations, or an event log, and each trades off simplicity, flexibility, and how much infrastructure a team needs to run themselves.

## Building a Local First Feature

The core loop behind most local first features follows a simple pattern: apply the change locally first, queue it, then sync it in the background.

```ts
interface Change {
  id: string;
  entity: string;
  payload: unknown;
  timestamp: number;
}

class LocalStore {
  private pending: Change[] = [];

  async write(entity: string, payload: unknown) {
    const change: Change = {
      id: crypto.randomUUID(),
      entity,
      payload,
      timestamp: Date.now(),
    };

    // Apply immediately so the interface updates without waiting on the network
    await this.applyLocally(change);
    this.pending.push(change);
    this.scheduleSync();
  }

  private scheduleSync() {
    if (!navigator.onLine) return;

    syncEngine.push(this.pending).then(() => {
      this.pending = [];
    });
  }

  private async applyLocally(change: Change) {
    // Persist to an on device store such as SQLite or IndexedDB
  }
}
```

The loop itself is straightforward. The real complexity in a production system sits around it: migrating a schema across devices that may be running different versions of the application at the same time, merging concurrent edits to the same field using a CRDT rather than simply overwriting one write with another, and handling authentication and per record permissions in a system where the client is allowed to write data before the server has had any chance to approve it.

## Local First Compared to Traditional Client Server Architecture

In a traditional client server application, every interaction waits on the network, going offline typically means the application stops working, and conflicting writes are usually resolved by whichever write reaches the server last.

A local first application behaves differently on all three counts. Interactions feel instant because they are applied to local storage first. Going offline does not break the experience, because the local copy is complete rather than a cache of something else. Conflicts are resolved automatically through CRDT merges instead of one user's change silently overwriting another's.

## Challenges of Local First Applications

The approach is not without real costs. Distributed systems complexity that used to live entirely on the server now lives partly on the client, and schema migrations have to account for multiple versions of an application running against the same synced data simultaneously.

Not every kind of data fits a CRDT cleanly. Operations such as enforcing a unique username or preventing a financial ledger from double spending require genuine coordination that a local merge cannot fully resolve on its own. Most production systems end up combining local first data for the bulk of the application with a smaller set of operations that still go through a coordinating server.

The tooling, while far more mature than it was even two years ago, still assumes a working familiarity with distributed systems concepts that many frontend teams have not needed before, and documentation across the ecosystem varies widely in how much of that background it assumes.

## When Local First Is Worth Adopting

The approach fits naturally with collaborative tools, note taking and writing applications, and any product that needs to work reliably on unreliable networks or fully offline. It is less necessary for simple administrative interfaces with steady connectivity and little to no collaboration, where the added complexity of a sync engine and a CRDT layer is unlikely to pay for itself.

## Conclusion

Local first architecture is not a replacement for the client server model in every situation, but the path to adopting it has matured enough by 2026 that teams no longer need to build a sync engine or a CRDT implementation from scratch to benefit from it. For frontend teams working on collaborative or offline sensitive products, understanding these concepts is becoming as fundamental as understanding server rendering was a decade ago.

## References

[Ink & Switch: Local First Software](https://www.inkandswitch.com/essay/local-first/)

[PowerSync Docs: Local First Software](https://docs.powersync.com/resources/local-first-software)

[Wikipedia: Local First Software](https://en.wikipedia.org/wiki/Local-first_software)

[Awesome Local First: A Curated List of Resources](https://github.com/alexanderop/awesome-local-first)

[HLD Handbook: CRDT Applications](https://hld.handbook.academy/curriculum/architecture-patterns/crdt-applications/)