WooriDB

USER GUIDE

WooriDB is a general purpose (EXPERIMENTAL) time serial database, which means it contains all entities registries indexed by DateTime. It is schemaless, key-value storage and uses its own query syntax that is similar to SparQL and Crux's Datalog.

If you want me to continue improving this project: Patreon link

Some other features are:

• Hashing keys content with ENCRYPT keyword.
• Hashed values are filtered out and can only be checked with CHECK keyword.
• Ron schemas for input and output.
  • JSON is supported via feature.
• Entities are indexed by entity_name (Entity Tree), DateTime (Time Serial) and Uuid (Entity ID). Entity format is a HashMap where keys are strings and values are supported Types.
• Stores persistent data locally.
• Able to handle very large numbers when using the P suffix.
  • Ex: 98347883122138743294728345738925783257325789353593473247832493483478935673.9347324783249348347893567393473247832493483478935673P.
• Configuration is done via environment variables.
• Authentication and Authorization via session token
• Conditional Update
• Some Relation Algebra
• Entity history

Woori means our and although I developed this DB initially alone, it is in my culture to call everything that is done for our community and by our community ours.

This project is hugely inspired by:

• Crux;
• Datomic;
• Prometheus
• SparQL.
• Database Internals
• Database System Concept
• Designing Data Intensive Application
• Professor Andy Pavlo Database classes.
• Zero Trust in Time Series Data?

Installation

To run WooriDB it is necessary to have Rust installed in the machine. There are two ways to do this:

1. Go to rustup.rs and copy the command there, for unix it is curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh.
2. Clone WooriDB and execute make setup.

Executing WooriDB

• Release mode performance: make release in project root for performance optimization.
• Release mode size: make run in project root for size optimization.
• Debug mode: make debug in project root.

Docker

you can find the latest docker image at naomijub/wooridb. The current most stable tag is beta-8. To execute the docker container run:

• docker run -p 1438:1438 naomijubs/wooridb:beta-8 debug for debug mode.
• docker run -p 1438:1438 -e AUTH_HASHING_COST=8 -e ADMIN=your-admin-id -e ADMIN_PASSWORD=your-admin-pswd naomijubs/wooridb:beta-8 run for size optimization.
• docker run -p 1438:1438 -e AUTH_HASHING_COST=8 -e ADMIN=your-admin-id -e ADMIN_PASSWORD=your-admin-pswd naomijubs/wooridb:beta-8 release for performance optimization.
• All -e/--env can be replaced by a --env-file path/to/your/.env. Your .envfile should contain the following fields:

HASHING_COST=16
PORT=1438
AUTH_HASHING_COST=8
ADMIN=your-admin-id
ADMIN_PASSWORD=your-admin-pswd

Usage

• Responses are in RON format. Support for JSON is via --feature json and EDN will be done later by using features.
• For now only persistent local memory is used. Support for S3, Postgres and DynamoDB will also be done later by using features.
• Precise floats or numbers larger than f64::MAX/i128::MAX can be defined with an UPPERCASE P at the end.
  • Note: This type cannot be updated with UPDATE CONTENT.
  • Ex.: INSERT {a: 98347883122138743294728345738925783257325789353593473247832493483478935673.9347324783249348347893567393473247832493483478935673P, } INTO my_entity.
• BLOB will not be supported. Check out To BLOB or Not To BLOB: Large Object Storage in a Database or a Filesystem.
• To configure hashing cost and port some environment variables are required:

HASHING_COST=16
PORT=1438

Milestone to stable-ish version

• issues

Current Benchmarks

2,3 GHz Intel Core i9 8-Core 32 GB 2667 MHz DDR4

• create_entity time: [4.7008 ms 4.7367 ms 4.7725 ms]
• insert_entity time: [12.647 ms 12.977 ms 13.308 ms]
• update_set_entity time: [14.896 ms 15.087 ms 15.309 ms]
• update_content_entity time: [14.871 ms 15.070 ms 15.307 ms]
• delete_entity time: [5.3966 ms 5.4423 ms 5.4908 ms] - Filtered 400s
• evict_entity_id time: [15.534 ms 15.623 ms 15.721 ms] - Filtered 400s
• evict_entity time: [12.318 ms 12.416 ms 12.540 ms] - Filtered 400s
• select_all 20 entities time: [6.3402 ms 6.4743 ms 6.6356 ms]
• select_all 10 entities time: [5.8318 ms 5.9682 ms 6.1340 ms]
• select_all 1 entity time: [5.1030 ms 5.1379 ms 5.1738 ms]
• history_10_registries_for_entity time: [5.4936 ms 5.5328 ms 5.5725 ms]
• history_20_registries_for_entity time: [6.0676 ms 6.1049 ms 6.1429 ms]

WQL

2,3 GHz Intel Core i9 8-Core 32 GB 2667 MHz DDR4

• create_entity time: [433.57 ns 435.00 ns 436.38 ns]
• inser_entity time: [1.6349 us 1.6406 us 1.6463 us]
• select_all time: [429.79 ns 431.05 ns 432.14 ns]
• select_args time: [655.40 ns 657.53 ns 659.71 ns]

File approximated size

For ~10000 entries in a day, the file size will be 2.5 GB for registries (and for cached values - this may become an issue soon). After compression it can be reduced to 10% of this.

artillery.io

2,3 GHz Intel Core i9 8-Core 32 GB 2667 MHz DDR4

Insert

Config file:

config:
  target: "http://localhost:1438"
  phases:
    - duration: 100
      arrivalRate: 10
  defaults:
    headers:
      Content-Type: "application/wql"
scenarios:
  - flow:
      - post:
          url: "/wql/tx"
          body: "INSERT {name: \"name\", last_name: \"last name\", age: 20, blood: 'O'} INTO person"

Select

Contains 1000 registries of {name: \"name\", last_name: \"last name\", age: 20, blood: 'O'}.

Config file:

config:
  target: "http://localhost:1438"
  phases:
    - duration: 100
      arrivalRate: 10
  defaults:
    headers:
      Content-Type: "application/wql"
scenarios:
  - flow:
      - post:
          url: "/wql/query"
          body: "SELECT * FROM person"