The Power of Sync Engines: Choosing the Right One for Your Next Project

In the rapidly evolving landscape of web development, applications are becoming increasingly complex, demanding seamless user experiences, real-time collaboration, and robust offline capabilities. Traditional client-server architectures often struggle to meet these demands efficiently, leading to challenges like data inconsistencies, slow loading times, and a poor user experience when network conditions are suboptimal. This is where sync engines emerge as a powerful paradigm shift.

What is a Sync Engine?

At its core, a sync engine is a system designed to synchronize data between multiple devices or services, acting as a persistent buffer between the frontend and the backend. It allows client-side applications to operate on a local, often optimistic, copy of the data, while intelligently managing the complexities of keeping that local state consistent with a remote, authoritative source. This involves handling network latency, offline scenarios, conflict resolution, and efficient data transfer.

Why are Sync Engines So Powerful?

Sync engines offer a multitude of benefits that can dramatically enhance the performance, responsiveness, and user experience of modern applications:

• Optimistic UI and Perceived Performance: By allowing the client to immediately update its local state in response to user actions, sync engines enable optimistic UI updates. This means users see their changes reflected instantly, even before the data is fully synchronized with the backend, leading to a perception of lightning-fast performance and a highly responsive application.
• Offline Capabilities: A key advantage of sync engines is their ability to enable robust offline functionality. Users can continue to interact with the application, make changes, and access data even without an internet connection. Once connectivity is restored, the sync engine seamlessly synchronizes the local changes with the remote server.
• Real-time Collaboration: For collaborative applications, sync engines are transformative. They facilitate real-time updates across multiple clients, ensuring that all users are working with the most current version of the data. This is often achieved through mechanisms like operational transformations (OT) or conflict-free replicated data types (CRDTs).
• Reduced Backend Load and Complexity: By offloading much of the data management and synchronization logic to the client-side and the sync engine, the backend can be simplified. The backend primarily becomes a data store and a conduit for synchronization, rather than being burdened with complex real-time state management for every connected client.
• Enhanced Developer Experience: Sync engines abstract away many of the complexities of data synchronization, network handling, and offline support, allowing developers to focus on building application features rather than wrestling with low-level data consistency issues.

What are the Drawbacks of Sync Engines?

While powerful, sync engines are not a silver bullet and come with their own set of challenges and considerations:

• Increased Frontend Complexity: While they simplify backend concerns, sync engines can introduce significant complexity to the frontend. Developers need to understand how the local store works, how data flows, and how to handle potential conflicts.
• Setup and Integration Overhead: Integrating a sync engine into an existing application or setting one up from scratch can involve a considerable initial overhead. This includes configuring the client-side library, setting up the backend components, and defining synchronization rules.
• Conflict Resolution: In collaborative environments or offline-first applications, conflicts can arise when multiple users modify the same data concurrently. Designing and implementing effective conflict resolution strategies can be challenging and requires careful consideration to avoid data loss or inconsistencies.
• Data Model Constraints: Some sync engines might impose specific constraints on the data model or require certain data structures to function optimally. This can sometimes necessitate adapting existing data models or designing new ones with the sync engine\‘s requirements in mind.
• Debugging and Observability: Debugging issues in a distributed system with local and remote states can be more complex than in traditional architectures. Understanding data flow, synchronization events, and potential discrepancies requires robust tooling and observability.
• Not Always Necessary: For simple applications with infrequent data updates or no offline requirements, the overhead and complexity introduced by a sync engine might outweigh its benefits. It\‘s crucial to assess whether the problem a sync engine solves truly exists for your specific project.

ElectricSQL Architecture and Features

ElectricSQL is a Postgres sync engine designed to enable local-first and reactive applications. It synchronizes subsets of your PostgreSQL data into local applications, services, and environments.

Key Components

Based on the information gathered, ElectricSQL’s architecture typically involves three main components:

1. PostgreSQL Extension: This component likely handles the server-side integration with PostgreSQL, enabling ElectricSQL to track changes and manage data synchronization from the database.
2. Sync Service (e.g., Elixir-based): This service acts as the central hub for synchronization, managing data flow between the PostgreSQL database and connected clients. It handles partial replication, fan-out, and data delivery.
3. Client-side Library (e.g., TypeScript): This library provides the interface for client applications to interact with the local data store and the sync service. It manages optimistic updates, local persistence, and synchronization with the backend.

Core Features

• Postgres Sync Engine: ElectricSQL is built specifically for PostgreSQL, allowing developers to leverage their existing Postgres databases for local-first applications.
• Partial Replication: It enables syncing only relevant subsets of data to local clients, optimizing performance and resource usage.
• Optimistic UI: Supports immediate UI updates on the client-side, providing a highly responsive user experience.
• Offline Capabilities: Applications built with ElectricSQL can function offline, with data synchronizing once connectivity is restored.
• Conflict Resolution (CRDTs): ElectricSQL utilizes Conflict-Free Replicated Data Types (CRDTs) to automatically merge changes and resolve conflicts, ensuring data consistency in collaborative and offline scenarios. This is a significant feature for local-first applications.
• Real-time Updates: Facilitates real-time data synchronization, making it suitable for collaborative applications.
• Open Source: ElectricSQL is an open-source project, allowing for transparency, community contributions, and self-hosting options.
• Integration with Frameworks: Provides integrations with popular frontend frameworks like React and data libraries like TanStack DB.
• Electric Cloud: Offers a managed cloud service for easier production deployment.

How it Works (High-Level)

1. The client application interacts with a local data store provided by the ElectricSQL client-side library.
2. Changes made locally are optimistically applied and persisted in the browser’s storage.
3. The sync service, running on the backend, pulls changes from PostgreSQL and pushes them to connected clients, and vice-versa.
4. CRDTs are used to handle concurrent modifications and ensure data consistency across all replicas.

ElectricSQL aims to simplify the development of local-first applications by abstracting away the complexities of data synchronization and conflict resolution, especially for PostgreSQL users.

Convex Architecture and Features

Convex is presented as an open-source, reactive database where queries are TypeScript code running directly within the database. It aims to provide a comprehensive backend solution for modern developers, offering a database, server functions, and client libraries.

Key Components

Convex’s architecture is built around a few core components:

1. Reactive Database: At the core of Convex is a reactive database that automatically provisions and manages itself. It’s described as a “document-relational” database, supporting JSON-like nested objects and relational structures with tables and references.
2. Server Functions: These are TypeScript functions that run directly within the database. They serve as the backend application logic and database query code, handling both read (query) and write (mutation) operations. This approach aims to reduce boilerplate and ensure type safety.
3. Client Libraries: Convex provides client libraries that enable frontend applications to interact with the database and server functions. These libraries handle automatic reactivity, managing subscriptions, WebSocket connections, and state synchronization.

Core Features

• TypeScript-native Development: Queries and mutations are written in TypeScript, providing end-to-end type safety.
• Transactional Guarantees: Ensures data consistency with read-only queries and transactional mutations.
• Automatic Reactivity: Automatically updates UI based on data changes, simplifying real-time features.
• Built-in Backend Services: Includes features like file storage, authentication, and scheduling, reducing the need for separate backend components.
• Optimistic Concurrency Control: Manages concurrent data modifications.

How it Works (High-Level)

1. Client applications interact with Convex through its client libraries.
2. Queries and mutations are executed as TypeScript server functions directly within the Convex database environment.
3. The reactive nature of the database ensures that any changes to data automatically trigger updates to dependent queries and client subscriptions.
4. Transactional guarantees and optimistic concurrency control maintain data consistency and integrity across the system.

Convex aims to provide a streamlined and reactive development experience by tightly integrating the database, backend logic, and frontend synchronization, particularly appealing to developers working with TypeScript and seeking a managed backend solution.

Convex’s Database Evolution: From MySQL to PostgreSQL

Convex, a backend-as-a-service (BaaS) platform, recently transitioned its underlying database infrastructure from Aurora MySQL to PlanetScale PostgreSQL. This move was driven by several key factors related to scalability, cost-efficiency, and multi-tenancy support.

Why the Switch to PostgreSQL?

Convex’s primary motivation for moving from Aurora MySQL to PlanetScale PostgreSQL stemmed from the limitations of their previous setup, particularly concerning multi-tenancy and cost-effectiveness for a free tier:

• Aurora MySQL’s Multi-Tenancy Limitations: Aurora MySQL instances are tightly coupled to a single MySQL instance, making it inefficient to run multiple independent databases per instance. This meant that each new Convex project (or tenant) required its own backend instance, leading to high costs and an inability to offer a cost-effective free tier.
• PlanetScale PostgreSQL’s Multi-Tenancy Support: PlanetScale, built on Vitess, added support for PostgreSQL, which allowed Convex to run multiple databases per instance. This capability is crucial for efficiently supporting multi-tenant applications and offering a viable free tier.
• Performance Improvements: The switch also brought significant performance gains, particularly in write latency. Convex reported that their P50 commit latency (median) became as good as their previous P99 (worst-case) commit latency, indicating a substantial improvement in real-time sync and write performance.

How Convex Uses PostgreSQL with a Document-Based Design

Convex describes itself as a “document-relational” database. This means it combines aspects of both document databases (like MongoDB) and relational databases (like PostgreSQL).

• Document Aspect: “Document” means that developers can store JSON-like nested objects within the database. This provides flexibility for handling semi-structured data, which is common in modern web applications.
• Relational Aspect: “Relational” implies that Convex supports tables with relations, allowing developers to link documents across different tables using IDs, similar to traditional relational database foreign keys.

While the article doesn’t explicitly state that Convex uses PostgreSQL’s JSONB fields, it is highly probable given PostgreSQL’s robust support for JSON data types and the benefits they offer for document-based designs. JSONB (JSON Binary) in PostgreSQL allows for efficient storage and querying of JSON data, treating it as a first-class data type rather than just a text string. This enables:

• Schema Flexibility: Developers can store arbitrarily complex JSON objects and arrays without predefined schemas, which is characteristic of document databases.
• Powerful Querying: PostgreSQL provides a rich set of functions and operators for querying and indexing JSONB data, allowing developers to perform complex queries on the nested document structures.
• Hybrid Approach: The combination of JSONB for document storage and traditional relational features (tables, relations) allows Convex to offer a flexible data model that can accommodate both structured and semi-structured data within a single system.

Convex’s Approach to Database Layers

It’s important to note that Convex doesn’t simply use PostgreSQL as a direct, exposed database. Instead, they maintain their own application-layer abstractions and custom optimizations, particularly in their Rust-powered internal data layer. This means:

• Swapping Storage Backend: Convex swapped out just the storage backend from Aurora MySQL to PlanetScale PostgreSQL, while keeping their higher-level query engine and relational schema layers intact.
• Custom Optimizations: They continue to manage the query layer and data layer logic with heavy custom optimizations, indicating that their implementation goes beyond a simple JSONB usage and involves sophisticated internal mechanisms to achieve their reactive and real-time capabilities.

In essence, Convex leverages PostgreSQL’s robust and scalable capabilities, including its JSON handling, as a powerful foundation for its reactive, document-relational database. The switch was a strategic move to enhance multi-tenancy support, improve performance, and provide a more cost-effective solution for their growing user base, all while maintaining their unique developer-centric platform.

Zero by Rocicorp Architecture and Features

Zero by Rocicorp is a new sync engine that distinguishes itself by being powered by queries. Instead of syncing entire tables or using static rules, Zero allows developers to write queries directly in client code, which can access the entire backend database.

Key Concepts and Architecture

Zero’s core innovation lies in its query-driven approach and the underlying technology that enables it:

1. Query-Powered Sync: Zero syncs data based on queries defined on the client-side. This means only the data relevant to the current queries is synchronized, leading to efficient data transfer and reduced overhead.
2. Local Caching and Instant Responses: Zero caches query data locally on the device. This local cache is then used to answer future queries instantly, providing a zero-millisecond response time for most user interactions. When a more specific query requires data not in the local cache, Zero automatically falls back to the server.
3. ZQL (Zero Query Language): This is a custom streaming query engine built by Rocicorp that enables efficient data synchronization. ZQL uses Incremental View Maintenance (IVM) on both client and server to efficiently keep complex queries up to date.
4. SQLite Replica: Zero maintains a SQLite replica of your data on the client side, allowing for offline capabilities and fast local access.
5. Horizontally Scalable, Stateful Web Service: The backend component of Zero is designed as a horizontally scalable, stateful web service, ensuring it can handle a growing number of clients and data.

Core Features

• Query-Driven Synchronization: Developers define what data to sync by writing queries directly in their client code, providing fine-grained control over data replication.
• Instant UI Updates: By leveraging local caching and optimistic updates, Zero aims to provide instant responses to user interactions, making applications feel highly responsive.
• Offline-First Capabilities: The local SQLite replica enables applications to function seamlessly offline, with changes synchronizing when connectivity is restored.
• Incremental View Maintenance (IVM): ZQL’s use of IVM ensures that only the necessary changes are synchronized, optimizing data transfer and reducing bandwidth usage.
• Postgres Support: Zero supports PostgreSQL as a backend database, allowing developers to integrate it with existing Postgres setups. It automatically adjusts table schemas on the replica.
• Custom Mutators: Zero provides a powerful mechanism for writing data through Custom Mutators, which are more flexible than traditional CRUD APIs.
• General-Purpose Sync: Zero aims to be a general-purpose sync engine, suitable for a wide range of web applications.

How it Works (High-Level)

1. The client application issues queries (ZQL) to retrieve data.
2. Zero first checks its local SQLite replica for the requested data. If available, it returns the data instantly.
3. If the data is not in the local cache or needs to be updated, Zero communicates with the backend service.
4. The backend service, a horizontally scalable web service, processes the queries and synchronizes the relevant data from the PostgreSQL database to the client.
5. IVM ensures that only the incremental changes are sent, keeping both client and server views efficient.
6. Data modifications are handled through Custom Mutators, providing a flexible way to write data back to the server.

Zero by Rocicorp focuses on providing a highly performant and flexible sync solution by putting queries at the forefront of its synchronization model, aiming for instant responsiveness and efficient data management.

Comparative Analysis of ElectricSQL, Convex, and Zero

This section provides a comparative analysis of ElectricSQL, Convex, and Zero, highlighting their architectural approaches, key features, and ideal use cases. While all three aim to solve data synchronization challenges, they do so with distinct philosophies and implementations.

1. ElectricSQL

Core Philosophy: ElectricSQL is a Postgres sync engine focused on enabling local-first applications directly on top of an existing PostgreSQL database.

Architecture:

• PostgreSQL-centric: Integrates deeply with PostgreSQL via an extension.
• Sync Service: A backend service (e.g., Elixir-based) manages synchronization between Postgres and clients.
• Client-side Library: Provides a local data store and handles optimistic updates and local persistence.

Key Features:

• Partial Replication: Syncs only relevant subsets of data to clients.
• CRDTs: Uses Conflict-Free Replicated Data Types for automatic conflict resolution, making it well-suited for collaborative and offline scenarios.
• Optimistic UI: Supports immediate UI feedback.
• Open Source: Offers flexibility for self-hosting and community contributions.
• Managed Cloud Option: Provides Electric Cloud for easier production deployment.

Ideal Use Cases:

• Applications already using or planning to use PostgreSQL as their primary database.
• Local-first applications requiring robust offline capabilities and automatic conflict resolution.
• Collaborative applications where multiple users might concurrently modify data.
• Developers who prefer a more hands-on approach with their database infrastructure.

2. Convex

Core Philosophy: Convex is a reactive database and a comprehensive backend solution that integrates database, server functions, and client libraries into a single, cohesive platform.

Architecture:

• Reactive Database: A managed, “document-relational” database that automatically provisions itself.
• Server Functions: Backend logic and database queries are written in TypeScript and run directly within the database environment.
• Client Libraries: Handle automatic reactivity, subscriptions, and state synchronization on the frontend.

Key Features:

• TypeScript-native Development: Queries and mutations are written in TypeScript, providing end-to-end type safety.
• Transactional Guarantees: Ensures data consistency with read-only queries and transactional mutations.
• Automatic Reactivity: Automatically updates UI based on data changes, simplifying real-time features.
• Built-in Backend Services: Includes features like file storage, authentication, and scheduling, reducing the need for separate backend components.
• Optimistic Concurrency Control: Manages concurrent data modifications.

Ideal Use Cases:

• Developers looking for a fully integrated backend solution that combines database, serverless functions, and sync capabilities.
• Applications requiring rapid development and deployment with a focus on real-time features and reactive UIs.
• Teams comfortable with TypeScript for both frontend and backend development.
• Projects where a managed service approach for the backend is preferred.

3. Zero by Rocicorp

Core Philosophy: Zero is a query-powered sync engine that prioritizes instant responsiveness and efficient data synchronization by allowing developers to define what data to sync through client-side queries.

Architecture:

• Query-Driven Sync: Data synchronization is based on queries (ZQL) defined in the client code.
• Local SQLite Replica: Maintains a local SQLite database on the client for offline capabilities and instant local access.
• ZQL (Zero Query Language): A custom streaming query engine utilizing Incremental View Maintenance (IVM) for efficient data updates.
• Horizontally Scalable, Stateful Web Service: A stateful web service on the backend handles queries and synchronization with the primary database.

Key Features:

• Instant UI Updates: Achieves near-zero latency for user interactions through local caching and optimistic updates.
• Fine-grained Synchronization: Only relevant data subsets are synced based on active queries, optimizing bandwidth and performance.
• Offline-First: Robust offline support due to the local SQLite replica.
• Incremental View Maintenance: Efficiently updates data by only sending incremental changes.
• Postgres Support: Integrates with existing PostgreSQL databases.
• Custom Mutators: Provides a flexible way to handle data writes and business logic.

Ideal Use Cases:

• Applications demanding extreme responsiveness and a seamless user experience, even with intermittent connectivity.
• Projects where precise control over data synchronization at the query level is desired.
• Developers who want to leverage their existing PostgreSQL setup while gaining advanced sync capabilities.
• Building complex, collaborative applications where efficient real-time updates are critical.

Comparison Summary

Choosing the Right Sync Engine for Your Project

Selecting the optimal sync engine depends heavily on your project`s specific requirements, existing technology stack, and team`s expertise.

• If you are heavily invested in PostgreSQL and prefer to maintain control over your database infrastructure, ElectricSQL is an excellent choice. Its deep integration with Postgres and reliance on CRDTs for conflict resolution make it ideal for local-first and collaborative applications built around a relational database.

• If you are looking for a comprehensive, managed backend solution that simplifies full-stack development with TypeScript, Convex stands out. Its integrated reactive database, server functions, and client libraries provide a cohesive development experience, especially for applications that benefit from automatic reactivity and real-time updates without managing separate backend components.

• If your primary concern is achieving unparalleled responsiveness and fine-grained control over data synchronization at the query level, Zero by Rocicorp is a strong contender. Its query-driven approach and focus on incremental updates make it suitable for highly interactive applications where instant UI feedback and efficient data transfer are paramount, particularly if you`re comfortable with its unique ZQL.

Consider the following questions when making your decision:

1. What is your existing database technology? (e.g., PostgreSQL, NoSQL, or starting fresh)
2. What level of control do you want over your backend infrastructure? (fully managed vs. self-hosted components)
3. How critical are offline capabilities and real-time collaboration for your application?
4. What is your team`s familiarity with TypeScript, SQL, or custom query languages?
5. What are your performance and responsiveness requirements? (e.g., near-zero latency for UI updates)
6. What is your budget and willingness to invest in setup and integration overhead?

By carefully evaluating these factors against the strengths of ElectricSQL, Convex, and Zero, you can make an informed decision that aligns with your project`s goals and sets you up for success in building modern, data-intensive applications.

Why Convex Opts for PostgreSQL with Document Design Over Pure Document Databases like MongoDB

Convex, while offering a document-relational database, has chosen to build its platform on top of PostgreSQL (specifically, PlanetScale PostgreSQL) rather than a pure document database like MongoDB. This decision is rooted in several key architectural and functional differences that align with Convex’s goals of providing a reactive, transactional, and developer-friendly backend-as-a-service.

Key Differences and Advantages of Convex’s Approach

Convex’s comparison with MongoDB highlights several areas where its approach, leveraging PostgreSQL’s capabilities, offers distinct advantages:

1. Transactional Guarantees:

   • Convex: Provides full ACID (Atomicity, Consistency, Isolation, Durability) compliance and transactional guarantees for all operations, even across multiple documents. This is a fundamental aspect of its design, ensuring data integrity and consistency without performance compromises.
   • MongoDB: While MongoDB has evolved to include transactional support, it is atomic only at the document level by default. Multi-document transactions require manual configuration of two-phase commits, which can impact performance and add complexity. Convex argues that using MongoDB’s transaction API removes many of the benefits of using a NoSQL database.

2. Real-time Capabilities and Consistency:

   • Convex: Offers real-time capabilities by default with automatic subscriptions for functions. Its WebSocket client provides strong consistency guarantees, ensuring that reads and writes are synchronized and consistent.
   • MongoDB: Is rolling out support for real-time subscriptions (e.g., with their Realm Web SDK), but this is a newer addition and may not offer the same level of integrated consistency guarantees as Convex’s native approach.

3. Backend-as-a-Service (BaaS) vs. Document Store:

   • Convex: Is a comprehensive BaaS that includes a database, serverless functions, file storage, cron jobs, and other features, allowing developers to write their entire backend directly in TypeScript.
   • MongoDB: Is primarily a document store/database. While powerful for data persistence, it requires integration with other products and services to build a complete backend, adding to development and operational overhead.

4. Type Safety and Developer Experience:

   • Convex: Provides end-to-end type safety from code to client, direct type inference, and autocompletion out of the box. It allows defining schemas at both the database and application levels in pure TypeScript.
   • MongoDB: Is largely an untyped document store. While ORMs can be used to define schemas at the application level, they often don’t provide the same level of end-to-end type safety as Convex’s integrated TypeScript approach.

5. Query Language and Abstraction:

   • Convex: Does not use a separate query language like SQL or MQL. Instead, developers use a native DB interface within TypeScript query functions, allowing for filtering and operations directly in code.
   • MongoDB: Uses its own query language (MQL) for data manipulation.

6. Multi-tenancy and Cost-Effectiveness:

   • As discussed previously, Convex’s move to PlanetScale PostgreSQL was largely driven by the need for better multi-tenancy support and a more cost-effective free tier. Traditional MySQL (and by extension, some pure document databases) can be inefficient for multi-tenant architectures where each tenant might require a separate database instance or complex sharding strategies.
   • PostgreSQL, especially with advancements like those in PlanetScale, offers more flexible and efficient ways to manage multiple databases within a single instance, which is crucial for a BaaS offering a free tier.

The Role of PostgreSQL’s JSONB

While Convex doesn’t explicitly state its internal implementation details, its document-relational model strongly suggests the use of PostgreSQL’s JSONB data type. JSONB allows PostgreSQL to store and query JSON data efficiently, providing a hybrid approach that combines the schema flexibility of document databases with the transactional and relational strengths of PostgreSQL. This enables Convex to:

• Leverage Relational Strengths: Benefit from PostgreSQL’s mature transactional capabilities, indexing, and relational features for structured data, which are often more robust than those found in pure document databases.
• Embrace Document Flexibility: Utilize JSONB to handle flexible, nested document structures, catering to the needs of modern web applications that often deal with evolving data schemas.
• Avoid MongoDB’s Transactional Overhead: By building on PostgreSQL, Convex can achieve strong transactional guarantees without the performance overhead or complexity associated with multi-document transactions in MongoDB.

Conclusion

Convex’s decision to build its reactive database on PostgreSQL, with a document-relational model, rather than a pure document database like MongoDB, is a strategic one. It allows Convex to offer a comprehensive backend solution that combines the best of both worlds: the schema flexibility and developer experience of document databases with the strong transactional guarantees, relational capabilities, and performance benefits of a mature relational database like PostgreSQL. This approach addresses some of the inherent limitations of pure document stores, particularly in scenarios requiring strict data consistency and complex relationships, while still providing the agility and responsiveness expected by modern application developers.

Sources

ElectricSQL - PostgreSQL sync engine for local-first applications
Convex - Reactive database and backend-as-a-service platform
Zero by Rocicorp - Query-powered sync engine with instant UI updates