MVP Search Endpoint Implementation

[davidgamez]

Description

As part of our API development, we must introduce a search endpoint. This is crucial for enabling users to perform Full-Text Search (FTS) actions on various fields spanning multiple entities. Detailed specifications and requirements can be found in #346.

Solutions

Two primary solutions emerge:

1. Utilizing a Full-Text Search Service
   Employing a specialized Full-Text Search service such as Solr or Elasticsearch presents a scalable and efficient approach. These platforms are designed to handle extensive search functionalities across vast datasets.

Pros:

• High Scalability: Capable of handling large datasets efficiently.
• Advanced Search Capabilities: Supports a wide range of search operators and queries out of the box.

Cons:

• Implementation Time: Requires significant time to integrate and configure.
• Increased Infrastructure Costs: Adding an additional service to our infrastructure introduces higher operational costs.
• Learning Curve: We can face a steep learning curve due to the complexity of these services.

Given our current database size (2000+ feeds), it is worth considering whether the immediate benefits justify the resource investment at this stage.

2. PostgreSQL Full-Text Search Capabilities
   Leveraging the Full-Text Search capabilities inherent to PostgreSQL offers a more straightforward and immediately accessible solution. PostgreSQL's FTS feature is built into the database, eliminating the need for external services and simplifying the implementation process.

Pros:

• Ease of Implementation: Integrates directly with our existing PostgreSQL database, facilitating a quicker setup.
• Cost-Effective: Utilizes existing infrastructure without the need for additional services, thus minimizing costs.
• Sufficient for Current Scale: Provides adequate performance and functionality for our current dataset size.

Cons:

• Scalability Concerns: While efficient for smaller datasets, it may not scale as seamlessly as dedicated FTS services for larger data volumes.
• Limited Search Features: Lack of advanced search capabilities and optimizations available in specialized search services.

Decision

Given our current database size and infrastructure, beginning with PostgreSQL's Full-Text Search capabilities seems the most pragmatic approach. It offers a balance of efficiency, cost, and ease of implementation suitable for our immediate needs. As our dataset grows and demands more sophisticated search functionalities, we can re-evaluate the necessity of integrating a dedicated Full-Text Search service like Elasticsearch or Solr.

[davidgamez]

I am closing this thread as a solution was selected.