DB Engine

A conceptual database engine toolkit, including a query language, indexes, and storage.

Concepts

DB Engine is a key/value store, where the value is a JSON object. It has the ability to store, index, and query data.

Querying the Database

There are two methods that DB Engine uses to query the data held by it: Indexes, and Full Table Scans.

Full Table Scans do just what it sounds like, they scan through the whole store, making comparisons. Full Table Scans use the following comparison mechanisms:

• equals - checks for equality
• gt - greater than
• gte - greater than or equal
• lt - less than
• lte - less than or equal
• between - lies in between or equal to

In addition, Indexes allow for faster queries, and are keyed against a single field in the data.

Indexes can expose other query operations for additional types of queries. This allows for expansion of other types of data and operations with the simple addition of an index.

Query Languages

DB Engine at the most basic level uses a tree based query language. Other query languages can be parsed and coerced into this form for consumption, including the built-in query language that is part of DB Engine.

Queries are built in JSON, and are descriptive.

{
  operand: "equals",
  key: "foo",
  value: "bar"
}

In this example, an equality check is done against the value contained in the foo field. If it matches with equality, then the result is returned.

{
  "foo": "bar",
  "baz": [
    1,
    2,
    3
  ]
}

This object would be matched.

Built-in Query Language

In addition, there is a built-in query language that is more semantic.

{
  "foo": "bar"
}

Parses out to:

{
  operand: "equals",
  key: "foo",
  value: "bar"
}

As does:

{
  "foo": {
    equals: "bar"
  }
}

Queries can have complex logic. When a query is using and or or, it allows for boolean logic:

{
  "$and": [
    {
      "$or": [
        {
          "name": {
            "equals": "Main"
          }
        },
        {
          "crime.type": {
            "equals": "Arson"
          }
        }
      ]
    },
    {
      "date": {
        "between": [ '2013-11-30', '2014-01-01' ]
      }
    }
  ]
}

This query finds any object that has a name field of "Main", plus any objects that have a crime.type of "Arson". The results of those are compared to the results of any objects that have a date between "2013-11-30" and "2014-01-01".

This query would parse to:

{
  operand: "$and",
  value: [
    {
      operand: "$or",
      value: [
        {
          operand: "equals",
          key: "name",
          value: "Main"
        },
        {
          operand: "equals",
          key: "crime.type",
          value: "Arson"
        }
      ]
    },
    {
      operand: "between",
      key: "date",
      value: [ '2013-11-30', '2014-01-01' ]
    }
  ]
}