Netflix/falcor

Features

• Data Source Unification - Represents multiple remote data sources as a single virtual JSON model for consistent access.
• Graph Data Models - Models remote data as a single unified virtual JSON graph for efficient path-based retrieval.
• Data Fetching Libraries - Functions as a data fetching library that models backend data as a unified virtual JSON graph.
• Batch Value Retrievals - Retrieves several values from the graph in a single operation and returns them as a combined object.
• Batch Value Updates - Updates several values in a single request using path-value pairs or a JSON envelope.
• Client-Side Cache Invalidations - Maintains a local cache and supports invalidating stale paths following mutation operations.
• Graph Querying - Allows queries to traverse a virtual JSON graph using path arrays to automatically resolve references.
• Path-Based Value Updates - Updates a specific value in the data source and reflects the change in the local cache.
• Path-Based Value Retrieval - Fetches a specific value from the data source or local cache using a provided path.
• Reference-Aware Caching - Stores graph fragments in a local cache with path-based invalidation and timestamp-based race condition prevention.
• Graph Reference Management - Implements a reference-aware graph model to handle many-to-many relationships and prevent data duplication.
• Path-Based Data Access - Retrieves specific data values using path syntax to read, update, or trigger actions.
• Unified Virtual JSON Graphs - Represents remote data as a single unified document where entities are accessed via globally unique identity paths.
• Virtual JSON Graph Clients - Models remote data as a single virtual JSON graph for efficient path-based querying.
• Virtual Graph Querying - Queries a unified virtual JSON document through a single endpoint to retrieve data from various backend services.
• Mutation-Based Cache Invalidation - Removes stale cached values by using a list of changed paths returned after a server-side function call.
• Unified Data Models - Represents multiple remote data sources as a single unified JSON graph for consistent access.
• Path-Based Query Engines - Provides a query engine for retrieving and updating specific values in a distributed model using unique identity paths.
• Remote Function Invocation - Enables the invocation of transactional server-side operations to mutate graph data.
• Virtual Graph Resolution - Traverses a virtual graph by following path arrays and automatically resolving references to locate data.
• Reference-Aware Path Mutations - Sets new values at specified paths in a graph model by automatically resolving references.
• Virtual JSON Modeling - Treats remote data as a virtual JSON resource to fetch specific paths without managing individual endpoints.
• Client-Side Caching - Implements a local cache to mirror remote graph state and minimize redundant network requests.
• Virtual Graph API Interfaces - Provides access to remote data using standard JavaScript operations like get, set, and call on a virtual graph.
• Virtual JSON Graph Interfaces - Exposes a unified data model through a standard interface for external service consumption.
• Collapsing Batch Requests - Merges multiple concurrent requests within a time window into a single network call to eliminate redundancy.
• Asynchronous Write Operations - Updates values in a graph object at specified paths and returns the modified subset asynchronously.
• Graph-to-JSON Converters - Converts internal graph formats into standard JSON objects after retrieving multiple values.
• Cache Priming - Supports pre-populating the local cache by fetching specified paths from the remote source.
• Graph Data Retrieval - Fetches JSON graph data from remote servers using HTTP or HTTPS protocols.
• Change Notifications - Triggers callback functions whenever data in the local cache is modified.
• Cache Expiration Management - Uses metadata to manage the time-to-live and expiration of cached graph fragments.
• Identity-Based Dereferencing - Creates a new model bound to a specific object by its identity to target entities correctly.
• Functional Reactive Cache Hooks - Provides custom callback functions to react to cache changes and transform incoming errors.
• Virtual Graph Data Loading - Fetches values for specific paths from a cache or remote source and loads them into an object.
• Partial Graph Queries - Queries specific paths from a resource to minimize data transfer and reduce network overhead.
• Pluggable Transport Backends - Implements a standard interface for data sources to allow any backend transport.
• Data Version Tracking - Provides incrementing version numbers to track changes at specific paths within the virtual graph.
• In-Stream Error Values - Reports errors as regular data values in the response stream instead of using separate error callbacks.
• Observable Streams - Wraps data retrieval and mutation results in observable streams that treat errors as regular data values.
• Timestamp-Based State Synchronization - Uses timestamps on values to ensure old network data does not overwrite newer local state.
• Nested Key Resolution - Accesses deeply nested values within a virtual JSON document using path-based key lookups.
• Request Batching - Collects multiple asynchronous data requests within a short interval and merges them into a single network call.
• Relative Graph Navigation - Creates model instances bound to specific locations to make subsequent data paths relative.
• Scoped Model Binding - Creates scoped model instances bound to specific graph locations to allow relative path access.
• Request Deduplication - Deduplicates requests during virtual graph traversal to reduce redundant data fetches.
• Request Routing - Maps incoming graph operations to server handlers that return data from a virtual JSON object.
• Virtual Resource Hosting - Hosts a virtual JSON document on a server that resolves data requests from multiple sources on demand.

Star 历史