Bagisto, is an open source eCommerce platform built on Laravel. It is designed to be flexible, strong, and ready to support growing businesses.
As product catalogs expand into the millions, maintaining high performance becomes a critical factor.
This blog shares smart tips to scale Bagisto for nearly 10 million products using strong database tuning, cache use, and smooth queue management.
Understanding the Challenges
When scaling an eCommerce store to handle millions of products, the challenges evolve as the product catalog grows.
With around 0.2 million products, the system performs smoothly, handling database queries and searches efficiently without the need for advanced optimizations.
At 10 million products, the database and search face heavy load, so tools like Elasticsearch and smart caching help keep speed fast and performance stable.
Key Challenges:
- Database Performance – Handling a massive volume of records efficiently without slowing down the system.
- Search Optimization – Ensuring that users can quickly find products, even with such a large catalog.
- Indexing & Caching – Reducing load times and improving response speed with proper indexing strategies and caching mechanisms.
Let’s explore how Bagisto, built on Laravel, handles these challenges and scales efficiently.
Database Performance in Bagisto
Bagisto uses MySQL or MariaDB by default. To manage 10 million products well, we must optimize the database and how the platform interacts with it.
Optimizing Database Queries in Bagisto
Bagisto uses Eloquent ORM for database queries. With large data, it may slow down, so proper tuning is needed to boost speed and performance.
- Eager Loading: Avoid N+1 query problems by using eager loading for relationships. This ensures that related models are loaded in a single query, eliminating the need for multiple queries.
- Batch Updates: When updating large sets of records (e.g., updating product prices or inventory), use batch processing to handle them in chunks, reducing the load on the database.
Indexing Strategies in Bagisto for Scalable Database Performance
Bagisto structures indexed data for efficient search and retrieval, storing product information in Elasticsearch as documents within indices.
Each document in an index represents a product or product-related data (like product name, price, description, etc.).
This structured approach allows Elasticsearch to efficiently manage and retrieve product information.
When a user searches in Bagisto, Elasticsearch checks indexed data to give fast and accurate results, improving speed and user experience.
To enhance Bagisto performance, the following indexers play a crucial role:
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Price Indexing: In Bagisto, price indexing keeps product prices up to date by syncing database changes, so storefront pricing stays correct and consistent.
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Inventory Indexing: In Bagisto, inventory indexing keeps product stock levels accurate by updating quantities in real time.
Bagisto automatically updates inventory when customers buy, return, or restock products, ensuring accurate stock display and consistent pricing rules.
- Flat Indexing: Flat indexing is a mechanism that optimizes product data retrieval. By processing products in batches, the system can handle large datasets efficiently without overloading the server. It’s particularly useful for managing large volumes of product attributes (e.g., SKU, price, weight) for various channels and locales.
- Catalog Rule Indexing: Catalog rule indexing updates product prices based on changes in catalog rules, such as expiring or modified offers. Bagisto schedules this indexing process daily at 00:01, ensuring that pricing remains accurate without requiring manual intervention.
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ElasticSearch: Elasticsearch handles large data and delivers fast, scalable search results. Bagisto uses it to index products and improve search speed.
Leveraging Elasticsearch for Scalable Search
A key part of scaling an eCommerce platform is keeping product search fast and efficient, even when the store has millions of products listed.
While MySQL/MariaDB handles basic queries, they struggle with full-text search and complex filtering on large catalogs, which is where Elasticsearch excels.
1. Why Elasticsearch?
Elasticsearch is a fast and scalable search engine with strong text search. Using it with Bagisto improves search speed and results.
- Full-Text Search: Elasticsearch provides powerful full-text search capabilities, making it faster and more efficient than relational databases.
- Scalability: With its distributed architecture, Elasticsearch can scale horizontally by adding more nodes.
- Real-Time Indexing: When products are added, updated, or removed, Elasticsearch allows for real-time indexing. This ensures that product searches reflect the most up-to-date information, crucial for a dynamic e-commerce environment.
Integrating Elasticsearch for Bagisto helps search performance scale smoothly as the product catalog continues to grow.
2. Integrating Elasticsearch with Bagisto
Integrating Elasticsearch with Bagisto is straightforward. First, configure your Elasticsearch instance and connect it through the admin panel.
Bagisto will automatically index products, including attributes like name, description, price, and availability.
Here’s a simple configuration for integrating Elasticsearch with Bagisto:
To configure Elasticsearch, please refer to the Configuration Setup documentation.
3. Real-Time Indexing and Synchronization
Elasticsearch indexes products in real-time, ensuring that Bagisto instantly reflects additions or updates.
This keeps product searches up-to-date, which is crucial in eCommerce environments where product information changes frequently.
- How Real-Time Indexing Works in Bagisto: When a product is updated in Bagisto—whether it’s a price change, stock update, or a new product—Elasticsearch quickly updates the search index.
This ensures customers always see the latest prices and availability in search results, improving their shopping experience. - Automatic Re-Indexing in Bagisto: Bagisto automatically updates Elasticsearch whenever products are added, updated, or deleted. This keeps search results accurate and in sync with the latest product data. Without this, users might see outdated prices or stock levels.
4. Final Performance Benchmark
Here’s a final benchmark of search performance and page load time after implementing Elasticsearch.
The image shows that the Home page loads in around 585.16 milliseconds with the 10 million products.
In the image below, you can see the Home page load time is around 561 milliseconds with the 10 million products.
In the below image below, you can see the category page load time around 516 milliseconds with the 10 million products.
Watch this video to scale your eCommerce project for massive growth without sacrificing speed or user experience.
Conclusion: Future Scalability Beyond 10 Million Products
Scaling Bagisto to handle 10 million products is a challenging but achievable task.
By improving the database with smart loading and batch updates, and using Elasticsearch for quick search, you can make your store smooth and high performing.
Leveraging advanced caching techniques further ensures that your Bagisto-powered store remains fast and responsive, even as the product catalog grows.
If you need custom solutions, hire a Laravel developer to build features for your store. Explore more Bagisto extensions and tools on official Bagisto website.
