Benchmark: Fly Json ODM - 1.19.0 - Query Performance

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/fly-json-odm@1.19.0/dist/flyjson.min.js"></script>

Script Preparation code:

var data = [];

var start = 1;
var end = 1000000;

// Build datatable
for(var i =start;i<=end;i++) {
  data.push({ id:i, name:'user_'+i });
}

// Set Datatable
var nosql1 = new FlyJson();
var query1 = nosql1.set(data);

var nosql2 = new FlyJson();
var query2 = nosql2.set(data);

var nosql3 = new FlyJson();
var query3 = nosql3.set(data);

var nosql4 = new FlyJson();
var query4 = nosql4.set(data);

var nosql5 = new FlyJson();
var query5 = nosql5.set(data);

Tests:

Where is the last user.
var result = query1.where('id',1000000).exec();
Where + Show 10 users with id above than 999990.
var result = query2.where('id', '>',999990).exec();
Show All Data but Limit to 10.
var result = query3.take(10).exec();
Get 10 last data.
var result = query4.orderBy('id', true).take(10).exec();
Paginate data to 10 item per page.
var result = query5.paginate(1, 10).exec();

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Where is the last user.
Where + Show 10 users with id above than 999990.
Show All Data but Limit to 10.
Get 10 last data.
Paginate data to 10 item per page.

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

I'll provide an explanation of the benchmark, options being compared, pros and cons of each approach, library usage, special JS features or syntax, and alternative approaches.

**Benchmark Overview**

The benchmark measures the performance of Fly Json ODM (Object Data Modeling) in a browser for various query operations. The test data consists of 1 million records with an "id" field and a "name" field. The benchmark script creates five instances of FlyJson, each populating the data set, and then executes different queries on each instance.

**Options Being Compared**

The benchmark compares four different query approaches:

1. **WHERE Clause**: `var result = query1.where('id', 1000000).exec();`
	* This approach filters records based on a specific condition.
2. **IN Operator**: `var result = query2.where('id', '>', 999990).exec();`
	* This approach filters records based on a range of values.
3. **LIMIT Clause**: `var result = query3.take(10).exec();`
	* This approach limits the number of records returned.
4. **ORDER BY and LIMIT Clauses**: `var result = query4.orderBy('id', true).take(10).exec();`
	* This approach orders records by a specific field and then limits the number of records returned.

**Pros and Cons of Each Approach**

1. **WHERE Clause**: Fastest, but may not be efficient for large datasets or complex queries.
	* Pros: Fast execution, simple to implement.
	* Cons: May not handle large datasets well, limited query complexity.
2. **IN Operator**: Slightly slower than WHERE Clause, but can handle larger datasets and more complex queries.
	* Pros: Can handle larger datasets, more flexible query syntax.
	* Cons: Slower execution, may require additional processing power.
3. **LIMIT Clause**: Fastest way to limit the number of records returned, but may not be efficient for large datasets or complex queries.
	* Pros: Fast execution, easy to implement.
	* Cons: Limited query complexity, may not handle large datasets well.
4. **ORDER BY and LIMIT Clauses**: Slower than other approaches, but provides more flexibility in querying the data.
	* Pros: More flexible query syntax, can handle larger datasets.
	* Cons: Slower execution, requires additional processing power.

**Library Usage**

The benchmark uses FlyJson, an Object Data Modeling library, to create and execute queries on the test data. FlyJson provides a simple and intuitive API for working with JSON-based data models.

**Special JS Features or Syntax**

None mentioned in this explanation.

**Alternative Approaches**

Other approaches to query optimization could include:

1. **Indexing**: Creating indexes on specific fields to improve query performance.
2. **Caching**: Caching frequently accessed data to reduce computation overhead.
3. **Parallel Processing**: Using multiple threads or processes to execute queries concurrently.
4. **Query Optimization Algorithms**: Implementing algorithms like query rewriting, pushdown, or materialization to optimize query plans.

These approaches could be explored as part of a larger optimization strategy, but are not currently being compared in this benchmark.

Related benchmarks:

Fly Json ODM - 1.19.0 - Query Performance (version: 0)

Benchmark using Fly Json ODM in browser for most common queries only.

Comparing performance of: Where is the last user. vs Where + Show 10 users with id above than 999990. vs Show All Data but Limit to 10. vs Get 10 last data. vs Paginate data to 10 item per page.

Created: 2 years ago by: Registered User

Jump to the latest result

Where is the last user.

Where + Show 10 users with id above than 999990.

Show All Data but Limit to 10.

Get 10 last data.

Paginate data to 10 item per page.

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):