Benchmark: Fly Json ODM - 1.8.4 Browser

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/fly-json-odm@1.8.4/dist/flyjson.min.js"></script>

Script Preparation code:

var nosql = new FlyJson();

var data = [];

var start = 1;
var end = 1000000;

for(var i =start;i<=end;i++) {
  data.push({ id:i, name:'user_'+i });
}

Tests:

SET + WHERE
var result = nosql.set(data).where('id',1000000).exec();
SET + WHERE (Shallow Mode)
var result = nosql.setMode('shallow').set(data).where('id',1000000).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

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

Measuring JavaScript performance is crucial for developing efficient and scalable web applications.

**Benchmark Overview**

The provided benchmark, hosted on MeasureThat.net, tests the performance of Fly Json ODM (Object Document Mapping) in a browser environment for large JSON arrays. The benchmark compares two approaches:

1. **SET + WHERE**: This method involves setting the entire JSON array using `nosql.set(data)` and then filtering the results using `where('id', 1000000).exec()`.
2. **SET + WHERE (Shallow Mode)**: This method uses a shallow mode configuration, which affects how the library processes the data.

**Options Compared**

The benchmark compares the performance of these two approaches:

*   **Performance**: The execution speed of each approach.
*   **Resource usage**: The amount of memory and CPU resources consumed by each approach.

**Pros and Cons of Each Approach:**

1.  **SET + WHERE**:
    *   Pros:
        *   Easy to implement and understand.
        *   Suitable for small to medium-sized datasets.
    *   Cons:
        *   Can be slower due to the overhead of filtering a large dataset.
        *   May consume more resources due to unnecessary data processing.

2.  **SET + WHERE (Shallow Mode)**:
    *   Pros:
        *   Can provide better performance for large datasets by optimizing data processing.
        *   May reduce resource usage compared to the standard approach.
    *   Cons:
        *   Requires a deeper understanding of the library's configuration options.
        *   Might introduce additional complexity in implementation.

**Library and Its Purpose:**

Fly Json ODM is a JavaScript library for working with JSON documents. It provides an object document mapping (ODM) system, which allows developers to store, retrieve, and manipulate data stored in JSON format.

The library's primary purpose is to simplify the process of interacting with JSON data by providing a familiar API similar to traditional relational databases.

**Special JS Feature or Syntax:**

There are no special JavaScript features or syntaxes used in this benchmark that would require additional explanation beyond their general understanding.

**Other Alternatives:**

Some alternative approaches for optimizing performance and resource usage when working with large JSON datasets include:

*   Using an optimized data processing library, such as Ramda or Lodash.
*   Implementing a custom filtering algorithm to minimize unnecessary data processing.
*   Utilizing caching mechanisms to reduce the load on the database (if applicable).
*   Employing parallel processing techniques to take advantage of multi-core processors.

These alternatives may require more advanced knowledge and implementation details, but they can potentially offer better performance and resource efficiency for complex use cases.

Related benchmarks:

Fly Json ODM - 1.8.4 Browser (version: 5)

Benchmark using Fly Json ODM in browser for 1million json array

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

Created: 6 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):