GopherDB is a new hybrid database which eases the creation, retrieval, and manipulation of data through a robust, yet simple query language. Being a hybrid database, individual tables can be configured to store data either only in memory, disk, or both. It features many table (AKA collection) types tailored for specific use-cases including secure user authentication, leaderboards for online games, keystores, ordered lists, and more.

Leveraging a comprehensive schema validation algorithm, your data is always kept well organized. Though this doesn't take away from your data structure's flexibility, meaning you can create any sort of object, nested schemas, and deep-nested data. Much like other No-SQL databases, GopherDB uses JSON as it's query/response language and means of storing data on the disk. Using standard JSON format, GopherDB provides a powerful new query language. Retrieve, manipulate, or run any combination of built-in methods on any piece of data in a table entry as a hierarchy of Object, Array, and Map. Not only is building queries easy, but the query format itself is more dynamic and expandable than any other JSON query format!

🚧 PROJECT IN DEVELOPMENT 🚧

• In-depth schema validation
• Standardized format across insert, update, and get queries
• Many useful methods for arithmetic, comparisons, list append/prepend, etc.
• Wide selection of data types and settings
• User authentication tables (single select queries only)
• Key-value tables (multi & single select queries)
• Ordered list tables (multi & single select queries)
• Leaderboards (multi & single select queries)

Recommendations: All feature recommendations will be taken into consideration. This includes new security features, data types, methods, table types, etc. (Security feature recommendations will be dealt with at the highest priority)

When creating a table in GopherDB, you will need to make a schema that describes what types of data the database will store, and how. These are all the data types available in GDB, and one or more must be used when creating a database schema:

• Boolean
• Unsigned Integer (8, 16, 32, and 64 bit)
• Integer (8, 16, 32, and 64 bit)
• Float (32 & 64 bit)
• String
• Array
• Map
• Object (AKA Schema)
• Time (AKA Date)

Binaries will be created when project is considered stable. For now, you must download and use the Go source with:

go get github.com/hewiefreeman/GopherDB

And the dependencies:

go get github.com/json-iterator/go (JSON-iterator)

go get github.com/schollz/progressbar(Progress Bar)

keystore is the only stable package as of right now. You can test all functionalities of the keystore package with this command from the keystore directory:

go test -v keystore_test.go

Get the "friends" Array for the key "Maya" on the "users" table:

// Query:
["Get", "users", "Maya", {"friends": []}]

// Output:
{"friends": [{"name":"Mary", "id": 2}, {"name":"Bill", "id": 1}, {"name":"Harry", "id": 0}]}

Get index 1 of the "friends" Array for the key "Maya" on the "users" table:

// Query
["Get", "users", "Maya", {"friends.1": []}]

// Output:
{"friends.1": {"name":"Bill", "id": 1}}

Get the name of index 1 of the "friends" Array for the key "Maya" on the "users" table:

// Query
["Get", "users", "Maya", {"friends.1.name": []}]

// Output:
{"friends.1.name": "Bill"}

Update the "friends" Array for the key "Maya" on the "users" table to be sorted alphabetically:

// ASC order
["Update", "users", "Maya", {"friends.*sortAsc": ["name"]}]
// DESC order
["Update", "users", "Maya", {"friends.*sortDesc": ["name"]}]

Append "George" to the "friends" Array for the key "Maya" on the "users" table:

// ASC order
["Update", "users", "Maya", {"friends.*append": [[{"name": "George", "id": 43523}]]}]

Add 10 then divide Maya's MMR by 2:

// ASC order
["Update", "users", "Maya", {"mmr.*add.*divide": [10, 2]}]