Benchmark: Fly Json ODM - 1.18.2 - Common Size

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/fly-json-odm@1.18.2/dist/flyjson.min.js"></script>

Script Preparation code:

var nosql = new FlyJson();

var data = [];

var start = 1;
var end = 100;

for(var i =start;i<=end;i++) {
  data.push({ id:i, name:'user_'+i });
}

Tests:

SET + WHERE
var result = nosql.set(data).where('id',100).exec();
SET + WHERE (Shallow Mode)
var result = nosql.setMode('shallow').set(data).where('id',100).exec();

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
SET + WHERE
SET + WHERE (Shallow Mode)

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 break down the explanation into sections for better understanding.

**Benchmark Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. The provided JSON represents a benchmark test case, which compares two approaches: setting data in Fly Json ODM (Object Document Model) with a shallow mode.

**Fly Json ODM Library**

The Fly Json ODM library is an object document model (ODM) system for JavaScript. It allows developers to store and retrieve data in a JSON-like format, similar to NoSQL databases. The library provides methods for setting, updating, and querying data.

In this benchmark, the Fly Json ODM library is used to store and query data on the client-side.

**Benchmark Test Cases**

There are two test cases:

1. **"SET + WHERE"`**: This test case sets the data using the `set` method and then queries it using the `where` method.
2. **"SET + WHERE (Shallow Mode)"`: This test case sets the data using the `setMode('shallow')` method, which enables shallow mode, and then queries it using the `where` method.

**Options Compared**

The two test cases compare the performance of setting data in Fly Json ODM with different modes:

* Shallow mode: This mode is optimized for faster query performance but may have limitations on data size.
* Normal mode: This mode is more flexible but may be slower than shallow mode.

**Pros and Cons**

Pros:

* Shallow mode:
	+ Faster query performance
	+ Smaller memory footprint
* Normal mode:
	+ More flexibility in data structure
	+ Easier to implement

Cons:

* Shallow mode:
	+ Limited support for complex queries
	+ May not work well with large datasets
* Normal mode:
	+ Slower query performance
	+ Larger memory footprint

**Other Considerations**

When choosing between shallow and normal modes, consider the following factors:

* Query complexity: If you need to perform complex queries, shallow mode might be a better choice.
* Data size: If you're working with large datasets, shallow mode can help reduce memory usage.
* Development ease: Normal mode is often easier to implement and understand.

**Alternative Approaches**

Other alternatives for setting data in JavaScript include:

* IndexedDB: A client-side storage system that provides a more robust query mechanism than Fly Json ODM.
* LocalStorage: A simple key-value store that can be used for small amounts of data.
* NoSQL databases like MongoDB or Couchbase: These databases provide more advanced query mechanisms and are suitable for larger datasets.

Keep in mind that each alternative has its own trade-offs and limitations, and the choice depends on the specific use case and requirements.

Related benchmarks:

Fly Json ODM - 1.18.2 - Common Size (version: 0)

Benchmark using Fly Json ODM in browser for common size array objects. Mostly common size array object that people put in memory is not more than 100 rows.

Comparing performance of: SET + WHERE vs SET + WHERE (Shallow Mode)

Created: 2 years ago by: Registered User

Jump to the latest result

SET + WHERE

SET + WHERE (Shallow Mode)

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):