Jazz

Jazz is a local-first relational database and synchronization framework designed for offline-capable applications. It functions as a reactive state management system that treats database records as the primary source of truth, automatically updating user interfaces in real time as underlying data changes.

The project distinguishes itself through a collaborative data synchronization model that utilizes row-level versioning to track branching edit histories. It implements a security engine based on identity-claim row security, which enforces granular permissions on individual records, and supports end-to-end field encryption to protect sensitive data at the source.

The system covers a broad range of distributed data capabilities, including relational schema definition via a domain-specific language, durable stream-based synchronization between local replicas and remote storage, and geo-optimized distributed hosting. It provides a programmable interface for standard database mutations and queries while ensuring consistency across different devices and environments.

Features

Relational Data Synchronization - Implements a synchronization framework using row-level versioning and durable streams for relational data.

Local-First Databases - Provides a local-first relational database that synchronizes local replicas with a cloud backend.

Reactive Data Queries - Treats database records as the primary source of truth with live queries that trigger interface updates upon data changes.

Branching Record Versions - Tracks a branching history of changes for every individual record to enable real-time collaboration.

Synchronization Streams - Syncs local database replicas with remote storage using a sequence of immutable change logs for offline consistency.

Database Change Subscriptions - Updates the user interface automatically by subscribing to incremental changes in relational database records.

Distributed Relational Synchronization - Keeps structured data consistent across multiple devices and environments using reactive queries and durable data streams.

Distributed State Synchronization - Maintains a reactive shared state between distributed environments using tunable consistency for global transactions.

Branching Version Histories - Supports real-time collaboration by maintaining a branching, versioned history for every individual row.

Local-First Replica Synchronization - Synchronizes a local database replica with remote storage in the background to keep state consistent across devices.

Offline Data Management - Enables users to create and edit data locally without a connection and sync changes when network returns.

Offline-First Persistence - Enables application functionality without network connectivity by syncing a local database replica with a remote cloud store.

Branching Histories - Implements a collaborative synchronization model using row-level versioning to track branching edit histories.

Data Synchronization and Consistency - Maintains consistent relational state across distributed clients using partial tables and durable streams.

Data Change Notifications - Automatically refreshes the user interface by notifying subscribers of updates to database state changes across the network.

Policy Enforcement - Validates data access by matching user identity claims against server-enforced row security policies.

Row Level Security - Enforces granular permissions on individual records using identity-claim row security.

End-to-End Encryption - Protects sensitive information with end-to-end encryption to ensure data is only readable by authorized parties.

Row-Level Security - Secures individual records using policies integrated with user identity claims to validate permissions.

Server-Enforced Access Policies - Defines server-enforced rules to permit or reject specific read and write requests.

Reactive State Management - Treats the relational database as the primary source of reactive state to automatically update user interfaces.

Database-Backed State - Update the user interface automatically as data changes by using a relational database interface as reactive state.

CRUD Operations - Provides a programmable interface to query, insert, update, and delete rows with filtering, sorting, and pagination.

DSL-Based Definitions - Uses a domain-specific language to define relational models and permissions as a single source of truth.

Data Revision Tracking - Maintains historical snapshots of data entries to enable auditing and reverting to previous states.

Schema Versioning - Translates between application versions using compatibility layers to update data models without downtime.

Database Mutations - Provides a programmable interface for standard database mutations including insertions, updates, and deletions.

Relational Data Modeling - Specifies column types, relations, and arrays using a DSL to establish a data model source of truth.

Geo-Optimized Distributed Hosting - Provides a fault-tolerant, geo-optimized system that scales cloud infrastructure based on actual usage.

Relation Access Restrictions - Blocks or allows read and write operations on relational data by defining server-enforced permissions.

Field Level Encryption - Supports end-to-end field encryption to protect sensitive data within the distributed database.

User Access Controls - Regulates data access and editing through authentication and granular permission controls.

DSL-Driven Generation - Uses a custom domain-specific language to generate relational models and permission sets from a single source of truth.

Schema Evolution Strategies - Provides compatibility layers to translate data models between application versions without interrupting service.

Real-Time Collaborative Editing - Provides automatic synchronization and versioned edit histories for simultaneous multi-user data editing.

garden-cojazz

Features

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