FoundationDB: Developer Recipes
From the webpage:
Learn how to build new data models, indexes, and more on top of the FoundationDB key-value store API.
- Blob: Store binary large objects (blobs) in the database.
- Bulk Loading: Efficiently load large external datasets into the database.
- Graph: Create a directed graph data structure.
- Hierarchical Documents: Create a representation for hierarchical documents.
- Multimaps: Create an multimap data structure with multiset values.
- Priority Queues: Create a data structure for priority queues supporting operations for push, pop_min, peek_min, pop_max, and peek_max.
- Queues: Create a queue data structure that supports FIFO operations.
- Ranked Sets: Create a data structure for a ranked set that supports operations to insert, delete, and check membership of an item, while also allowing a client to find the rank of an item or retrieve items by rank.
- Rapid Updates to a Single Item: Update a single item in the database very rapidly.
- Segmented Range Reads: Perform range reads in calibrated batches.
- Simple Indexes: Add (one or more) indexes to allow efficient retrieval of data in multiple ways.
- Spatial Indexing: Create a spatial index for the database.
- Subspace Indirection: Employ subspace indirection to manage bulk inserts or similar long-running operations.
- Tables: Create a table data structure suitable for sparse data.
- Vector: Create a vector data structure.
I was musing the other day about how to denormalize a data structure for indexing.
This is the reverse of that process but still should be instructive.
Graphistas should note that FoundationDB also implements the Blueprints API (blueprints-foundationdb-graph).