It selects purchase-order documents that have a User field whose value is One part of a filter while leaving another part scoped at the document (context-item) level. The following SQL data types are supported for such variables: VARCHAR2, NUMBER, BINARY_DOUBLE, DATE, TIMESTAMP, and TIMESTAMP WITH TIMEZONE.Įxample 14-5 JSON_EXISTS: Path Expression Using The optional filter expression of a SQL/JSON path expression used with json_exists can refer to SQL/JSON variables, whose values are passed from SQL by binding them with the PASSING clause. The second argument to json_exists is a SQL/JSON path expression followed by an optional PASSING clause and an optional error clause. Unlike the case for conditions is json and is not json, condition json_exists expects the data it examines to be well-formed JSON data. The handler takes effect when any error occurs, but typically an error occurs when the given JSON data is not well-formed (using lax syntax). You can also use json_exists to create bitmap indexes for use with JSON data - see Example 24-1.Įrror handlers ERROR ON ERROR, FALSE ON ERROR, and TRUE ON ERROR apply. If no JSON values are matched then it returns false. More precisely, json_exists returns true if the data it targets matches one or more JSON values. Jump into the docs to understand EdgeDB in all its glory.Condition json_exists checks for the existence of a particular value within JSON data: it returns true if the value is present and false if it is absent. EdgeDB ships with a first-party interactive migration tool baked directly into the `edgedb` command-line tool.īut there are a hundred cool and nifty ways we’ve upgraded the developer experience of creating, querying, and managing databases. Hundreds of libraries across dozens of language ecosystems have tried to solve the problem of SQL migrations. Migrations have been a pain point for developers since the introduction of SQL. The EdgeDB spec includes a schema definition language (simply called the EdgeDB SDL) that lets you define your schema declaratively and succinctly, including advanced features like abstract types, computed fields, unions, custom scalars, and JSON support.įirst-party migrations. This includes support for GraphQL-style selection sets, easily nestable subqueries (including inserts and updates), a new link concept that abstracts away JOINs and foreign keys, edge properties, and a typesafe NULL-free type system grounded in set theory.ĭeclarative schema.
The EdgeQL query language: a full redesign of SQL that has been sorely needed for decades. As a rough structure, we consider the main innovations to be three-fold: There are a lot! Scroll down to the "Showcase" below for a bunch of examples. It lets EdgeDB take full advantage of the power of Postgres, whereas ORMs cannot their capabilities are limited to features shared by all the databases they support. And it was designed from the start as a new abstraction on top of Postgres specifically. If you cannot guarantee that the casting is always performed in your statement, you pass ::json and the operators can be used. If PostgreSQL can implicitly convert the parameter to json then you can omit ::json. It's language agnostic: you can interact with your database with any programming language you like. The operators ->, ->, > and > require the input datatype json. You query and manipulate data with a full-featured query language (EdgeQL) that is designed to match or surpass the power of SQL (though certain advanced features are still under development, see the Roadmap for details). provides an object-oriented way to perform and persist data manipulationsĮdgeDB has none of these properties.
is less capable than the query language is abstracts away (usually SQL).
In contrast, ORMs are libraries that provide a high-level way to query and manipulate data in your database. EdgeDB takes this concept one level further: it treats PostgreSQL as a lower-level storage engine and introduces better schema and query abstractions on top. In the case of most databases, these mechanisms are often low-level key-value stores (for example, WiredTiger in MongoDB, InnoDB in MySQL, or RocksDB in CockroachDB). Like every database throughout history, EdgeDB introduces a layer of abstraction on top of more primitive mechanisms performing data access and manipulation.