Features/Roadmap

[WolfDan]

Features/RoadMap

An issue describing short and long term features as well the roadmap

Short term goals

• Property Values

  • Primitive types List
  • I18N Strings (for this we need string indexing in order have sense, otherwise is just a property with and @ and the language at the end, so far theres no solutions for this on the erlang/elixir ecosystem, I don't know too much about the topic either, so futher discussions/PRs are welcome)
  • Enums
  • Dictionary (Use a node)
  • Datetime
  • Time
  • Date

• Index

  • Datetime
  • Enum
  • Time
  • Date
  • List
  • String (Exact match)
  • String (Hash match)
  • String (Full text search)
  • Integer
  • Float
  • Dictionary (Use a node)

• Node implementation

  • Update
  • Delete
  • One to One relationships! (User <--> UserConfig)
  • Set data
  • Get data
  • Index property edges
  • Inverse Node support (relation.uid, "edge_name", node.uid) = node_relation_edge.uid

• Edge implementation

  • Index property edges
  • Update
  • Delete
  • Set data
  • Get data

• Query support

  • where

    • Datetime storage { year, month, day, seconds }
    • > KeySelector.first_greater_than(key)
    • < KeySelector.last_less_than(key)
    • == get_by_function(property, value, function = Function.equal)
    • >= KeySelector.first_greater_or_equal(key)
    • <= KeySelector.last_less_or_equal(key)
    • and
    • or

  • pagination support (cursor based)

    • after Transaction.get_range(after_cursor, end, limit)
    • before Transaction.get_range(before_cursor, end, limit, reverse=True)
    • limit
    • first Transaction.get_range(start, end, limit=first)
    • count

  • sorting

    • order_asc index query
    • order_des index query

  • reverse node

  • functions

    • min atomic
    • max atomic

• Ztandart data compression

  Compress long sized strings in order to save space, unnoticeable performance impact

Long term goals

• Types check!

• More tests

Maybe

• Network Protocol implementation

  • GraphQL (standard query, mutation language) [this uses the connection
    features of GraphQL to make it easier to query graph data]
  • Opengraph (complex query for things like recommendation engines etc)

• query optimization/planning, what most databases does.