Features

• Sintax inspired by SparQL and Crux's datalog.
• Entities are indexed by date(time).
• Schemaless.
• Deep Key-value storage, which means that you can have key values inside hashmap values.
• Hashing entity map keys content with ENCRYPT.
• Unique entity maps keys content with UNIQUE for an entity tree.
• Hashed values are filtered out of SELECT and can only be checked with CHECK keyword.
• Ron schemas for input and output.
  • JSON is supported via feature.
  • EDN to be supported via feature.
• Entities are also indexed by entity_name (entity tree key) and Uuid (entity id). Entity map format is a HashMap where keys are strings and values are supported Types.
• Stores persistent data locally.
  • S3 as a backend is to be developed.
  • DynamoDB as a backend is to be developed.
• Able to handle very large numbers when using the P suffix.
  • Ex: 98347883122138743294728345738925783257325789353593473247832493483478935673.9347324783249348347893567393473247832493483478935673P.
• Configuration is done via environment variables.
  • CORS
• Authentication and Authorization via session token
• Users created and deleted by ADMIN user.
• Conditional Update
• File compression done with zstd.
• Entity id history
• Possible Relation Algebra
  • Union by entity_id
  • Intersection by entity_id
  • Difference by entity_id
  • Join
  • Dedup
  • Sort
  • Aggregate

Naming conventions:

• Entity Tree is similar to SQL table, it is the data structure that contains all ids and entities map relations.
• Entity ID is the id of an entity inside Entity tree.
• Entity map is the content of and entity associated with the entity id.