README

agdb

The graph database.

  Agnesoft Graph Database

Quickstart Db | Quickstart Client | QUERIES | DECISION TREE

Why not SQL?

The Agnesoft Graph Database (aka agdb) is application native database without compromises. It is persistent, optionally memory mapped graph database with native object 'no-text' queries. It can be used as a main persistent storage, data analytics platform as well as fast in-memory cache. Its typed schema-less data store allows for flexible and seamless data updates with no downtime or costly migrations. All queries are constructed via a builder pattern or directly as objects with no special language or text parsing.

• Key Features
• At a glance
• Crate Features
• Decision Tree
• Roadmap
• Reference

  Key Features

• The agdb is application native database.
• No query language, queries are written in the same language as the application.
• Performance without limits, constant time lookups and traversals regardless of db size.
• Simple to build, use & scale.

Technical features:

• Data plotted on a graph
• Typed key-value properties attached to graph elements (nodes & edges)
• Persistent platform agnostic file based storage (transferable between platforms)
• ACID compliant
• Object queries with builder pattern (no text, no query language)
• Memory mapped for fast querying
• Server mode
• Cluster mode
• In-built TLS support
• OpenAPI clients in any programming language
• Cloud hosted SaaS database
• Db itself has no dependencies

  At a glance [Db]

cargo add agdb

Basic usage demonstrating creating a database, inserting graph elements with data and querying them back with select and search. The function using this code must handle agdb::DbError for operator ? to work (i.e. fn foo() -> Result<(), agdb::DbError>):

use agdb::{Db, DbId, QueryBuilder, DbType};

let mut db = Db::new("db_file.agdb")?;

db.exec_mut(QueryBuilder::insert().nodes().aliases("users").query())?;

#[derive(Debug, DbType)]
struct User { db_id: Option<DbId>, name: String, }
let users = vec![User { db_id: None, name: "Alice".into(), },
                 User { db_id: None, name: "Bob".into(), },
                 User { db_id: None, name: "John".into(), }];

let users_ids = db.exec_mut(QueryBuilder::insert().nodes().values(&users).query())?;

db.exec_mut(
    QueryBuilder::insert()
        .edges()
        .from("users")
        .to(&users_ids)
        .query(),
)?;

This code creates a database called user_db.agdb with a simple graph of 4 nodes. The first node is aliased users and 3 user nodes for Alice, Bob and John are then connected with edges to the users node. The arbitrary name property is attached to the user nodes. Rather than inserting values directly with keys (which is also possible) we use our own type and derive from agdb::DbType to allow it to be used with the database.

You can select the graph elements (both nodes & edges) with their ids to get them back with their associated data (key-value properties). Let's select our users and convert the result into the list (notice we select only values relevant to our User type with passing User::db_keys()):

let users: Vec<User> = db
    .exec(
        QueryBuilder::select()
            .elements::<User>()
            .ids(&users_ids)
            .query(),
    )?
    .try_into()?;

println!("{:?}", users);
// [User { db_id: Some(DbId(2)), username: "Alice" },
//  User { db_id: Some(DbId(3)), username: "Bob" },
//  User { db_id: Some(DbId(4)), username: "John" }]

You can also search through the graph to get back only certain elements based on conditions. For example:

let user: User = db
    .exec(
        QueryBuilder::select()
            .elements::<User>()
            .search()
            .from("users")
            .where_()
            .key("name")
            .value("Bob")
            .query(),
    )?
    .try_into()?;

println!("{:?}", user);
// User { db_id: Some(DbId(3)), username: "Bob" }

For database concepts and primitive data types see concepts. For comprehensive overview of all queries see the queries reference or continue with more in-depth efficient agdb.

  Crate Features

agdb

agdb_api

agdb_server

  Decision Tree

flowchart TD;
    A[Embedded or server?] --> Embedded
    A --> B[Client or hosting?]
    Embedded --> Studio[<a href='https://agdb.agnesoft.com/docs/references/studio'>Studio</a>]
    Embedded --> Queries[<a href='https://agdb.agnesoft.com/docs/references/queries'>Queries</a>]
    B --> Client
    B --> Hosting
    Client --> API[<a href='https://agdb.agnesoft.com/api-docs/openapi'>API</a>]
    Client --> Studio
    Client --> Queries
    Hosting --> Server[<a href='https://agdb.agnesoft.com/docs/references/server'>Server</a>]
    Hosting --> Cloud[<a href='https://agdb.agnesoft.com/enterprise/cloud'>Cloud</a>]

  Roadmap

The following are planned features:

  Reference

• API

• But why?

• Cloud

• Concepts

• Efficient agdb

• Guides

• Performance

• Queries

• Server

• Studio

• Troubleshooting