Exabase is a high performance NOSQL database with ACID complaint and scalable.

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Rationale

Exabase provides support for these features:

• JSON based query language.
• ACID Compliant queries.
• Batch large writes (INSERT, DELETE, UPDATE) as a single query.
• Efficient data format.
• Efficient backup system and recovery.
• High performance and tunable scalability.
• Swappable storage engine (as part of plugin system).
• Totally Open sourced and free
• Backed and maintained by big minds at Uiedbook
• Super Fast Growing ecosystem

Exabase is designed as a simple, light and but powerful database, using the an intuitive schema, and a concise JSON base query format.

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How Exabase works

Exabase achieves a high degree of efficiency by employing the following techniques.

• Separation of concerns mechanism across tables. This allows for more efficiency by keeping each table manager in it own space.

• Exabase uses the most efficient storage mechanism which includes message-pack's serialization and linux based archiving.

• Exabase make an extensive use of Binary search algorithms and custom Binary inset algorithms, allowing for sorted storage and efficient query of data.

• Exabase employs log file managers and handles log file resizing to makeup for efficient memory usage, log files are totally resizable and durable.

• Consistency and Durability in log files and other very important files is achieved through an ACID complaint data processing mechanism which is optimized for crash recovery and consistency checks out of the box.

• Exabase achieves a high search query efficiency using a search indexing mechanism called Xtree, written from the ground up.

• Exabase excels at sorting data very fast using a combination of bucket & mergesort algorithms.

Requirements to use Exabase.

Exabase support all server-side Javascript runtime:

• Nodejs.
• Bunjs.
• Denojs.

How to get started with Exabase database.

Installation

Install Exabase right on your project using npm.

npm i exabase --save

Usage

Exabase is for the cave man, it has carefully designed APIs that allows you to make the most actions against your database in a very easy way.

When improvements and changes rolls out, we will quickly update this page and the currently prepared web documentation.

Using Exabase

The Exabase class accepts an object argument with the following options:

Options

export type ExabaseOptions = {
  /**
   * Exabase database
   * ---
   * name  */
  name?: string,
  /**
   * Exabase database
   * ---
   * RCT Memory cache percentage  */
  EXABASE_MEMORY_PERCENT?: number,
};

Exabase JSON Query format

Exabase is queried with json. in the format

{
  "table": "<table name>",
  "<query key>": "<query info>"
}

ExaSchema Query Properties

 {
  table: string;
  one?: string;
  sort?: {
    [x in keyof Partial<Model>]: "ASC" | "DESC";
  };
  many?: true;
  search?: Partial<Model>;
  insert?: Record<string, any>;
  update?: Partial<Model>;
  delete?: string;
  populate?: Record<string, any>;
  skip?: number;
  take?: number;
  count?: Record<string, any> | boolean;
};

Example syntax

const user = await db.query(
  JSON.stringify({
    table: "USER",
    insert: { name: "james bond" },
  })
);

const user2 = await db.query(JSON.stringify({ table: "USER", one: user._id }));
expect(user.name).toBe("james bond");
const user3 = (
  await db.query(
    JSON.stringify({
      table: "USER",
      search: { name: user.name },
    })
  )
)[0];
const user4 = await db.query(
  JSON.stringify({
    table: "USER",
    update: { ...user, name: "gregs pola", age: 47 },
  })
);
await db.query(JSON.stringify({ table: "USER", delete: user._id }));
const user5 = await db.query(JSON.stringify({ table: "USER", one: user._id }));

expect(user._id).toBe(user2._id);
expect(user._id).toBe(user3._id);
expect(user._id).toBe(user4._id);
expect(user4.name).toBe("greg pola");
expect(user5).toBe(undefined);

A Basic Database setup and queries.

import { Exabase } from "../dist/index.js";

const db = new Exabase();

await db.query(
  JSON.stringify({
    table: "USER",
    induce: {
      age: { type: "number", required: true, index: true },
      name: { type: "string", index: true },
      kids: {
        relationType: "MANY",
        type: "string",
        target: "CHILD",
      },
    },
  })
);

await db.query(
  JSON.stringify({
    table: "CHILD",
    induce: {
      age: { type: "number", required: true, index: true },
      name: { type: "string", index: true },
    },
  })
);

const user = await db.query(
  JSON.stringify({
    table: "USER",
    insert: {
      age: i + 20,
      name: "user name",
    },
  })
);
const kid = await db.query(
  JSON.stringify({
    table: "CHILD",
    insert: {
      age: 5,
      name: "kid name",
    },
  })
);
user.kids.push(kid);

await db.query(
  JSON.stringify({
    table: "USER",
    update: user,
  })
);

Benchmarks

This benchmark is Exabase against sqlite.

Sqlite has a tiny footprint and off course really great performance with pure acidity and relational.

We are trilled Exabase performs really well and exceeding beats sqlite.

And with this confidence we have and encourage everyone to try Exabase for themselves.

cpu: Intel(R) Celeron(R) CPU 4205U @ 1.80GHz
runtime: bun 1.0.0 (x64-linux)

benchmark time (avg) (min … max) p75 p99 p995

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SELECT _ FROM "Employee" Exabase 1.39 µs/iter (1.23 µs … 3.77 µs) 1.35 µs 3.77 µs 3.77 µs
SELECT _ FROM "Employee" sqlite 270.73 µs/iter (187.72 µs … 3.24 ms) 267.24 µs 1.19 ms 1.48 ms
150X faster

Regularity Cache Tank

The Regularity Cache Tank or RCT is a basic LOG file level cache. this means, it stores the entire LOG(n) file of the table in memory, where n is the last active LOG file.

Apache 2.0 Licensed

Opensourced And Free.

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Contribution and License Agreement

If you contribute code to this project, you are implicitly allowing your code to be distributed under the Apache License. You are also implicitly verifying that all code is your original work.