How to Reduce App Load Times with Data Optimization

Slow app load times are one of the fastest ways to lose users—and often, the root cause is inefficient data handling. Whether you're building a customer-facing mobile app or an internal business tool, optimizing how your app retrieves, stores, and displays data can mean the difference between an engaged user base and an abandoned project. The challenge intensifies when you're managing apps across multiple platforms, where performance issues must be solved separately for web, iOS, and Android.

A no-code platform with built-in performance optimization makes tackling these challenges significantly easier. Adalo is a no-code app builder for database-driven web apps and native iOS and Android apps—one version across all three platforms. AI-assisted building and streamlined publishing enable launch to the Apple App Store and Google Play in days rather than months. This unified approach means every data optimization you implement automatically improves load times across all your platforms at once.

Why Adalo Works for Building Fast, Data-Optimized Apps

Adalo is a no-code app builder for database-driven web apps and native iOS and Android apps—one version across all three platforms, published to the Apple App Store and Google Play. This unified architecture means every data optimization technique you implement instantly improves load times across all your platforms simultaneously—maximizing your efforts without requiring separate codebases or duplicate work.

When you're managing database-driven applications, efficient data handling is critical for performance. Adalo's visual development environment lets you implement optimization strategies like pagination, caching, and streamlined queries without writing complex code. The result? Faster apps that keep users engaged across web browsers and mobile devices alike, with native app store distribution ensuring your optimized experience reaches users wherever they are.

Every second counts when it comes to app performance. Research shows that 53% of users abandon an app if it takes more than 3 seconds to load—and those lost users rarely come back. The culprit behind sluggish load times? Often, it's how your app handles data. The good news is that smart data optimization techniques can slash load times by up to 70%, transforming frustrated users into loyal customers.

In this guide, you'll learn six proven strategies to dramatically improve your app's performance: from streamlining data collections and writing efficient queries to implementing pagination, optimizing images, leveraging caching, and flattening data structures. Whether you're dealing with hundreds or thousands of records, these approaches will keep your app responsive and your users engaged.

If you're building with Adalo, an AI-powered app builder for database-driven web apps and native iOS and Android apps, these optimizations become even more powerful. The platform lets you publish to the App Store and Google Play from a single editor, meaning every data optimization you implement benefits all three platforms simultaneously—tripling your return on effort. Let's dive into the techniques that will make your app faster and your users happier.

Why Adalo Works for Building Fast, Optimized Apps

Adalo's unified approach means that every data optimization technique you implement instantly improves performance across your web app, iPhone app, and Android app simultaneously—maximizing the impact of your efforts without requiring separate codebases or duplicate work. With the Adalo 3.0 infrastructure overhaul launched in late 2026, apps now run 3-4x faster than before, with modular infrastructure that scales alongside your app's needs.

When your app loads quickly across all platforms, users stay engaged longer and are more likely to return. With native app publishing capabilities, you can combine optimized data handling with powerful features like push notifications to re-engage users and drive retention. The platform's paid plans now include unlimited database records—no caps, no restrictions—so you can focus on building great experiences rather than worrying about hitting data limits. Let's explore the specific strategies that will transform your app's performance.

Streamlining Data Collections and Queries

Organizing Data Collections Efficiently

Choosing the right database integration options and building a well-structured database can dramatically improve load times. Instead of creating separate collections for similar items—like Shoes, Pants, and Shirts—combine them into a single "Clothing Pieces" collection and use a category property to differentiate them. This reduces the number of database relationships and simplifies the queries your app needs to process.

Adalo's relational database tools make it easy to organize data effectively. By using one-to-many relationships, such as linking one User to multiple Posts, you can avoid unnecessary duplication. For example, assigning a User ID as a foreign key not only cuts down on redundancy by 30–50% in many apps but also speeds up queries by focusing on the exact data you need to retrieve.

Another smart tactic is to pre-calculate metrics like counts and sums rather than applying dynamic filters every time a screen loads. Store these values in a dedicated property and update them only when the data changes. As noted in Adalo's documentation:

Creating counts with filters on a list record is similar to creating a list within a list which will decrease your app's performance score.

Once your collections are streamlined, the next step is to refine your queries for even faster performance.

Writing Optimized Queries

After organizing your data, focus on writing efficient queries. Use server-side filtering to fetch only the data you need. For instance, instead of loading all records and filtering them on the client side, query for "Users where status = 'active' and city = 'New York'." Sorting on indexed fields, like dates, and limiting results to smaller sets—such as 10 to 50 items—can significantly reduce data transfer. For example, querying "Products: price < $50, sorted by popularity, limit 20" can cut data transfer by 80% compared to loading everything.

Fetching large datasets client-side can cause major delays. For example, loading 10,000 users on the client side might take up to 10 seconds. In contrast, a server-side query like "Users where last_login > 30 days ago, limit 100" can load in under a second. To further optimize, use "Is equal to" filters for quick matching and reserve more resource-intensive options like "Contains" for cases where they're absolutely necessary.

Using Adalo's Query Tools

Adalo's visual tools make it easier to implement these advanced optimizations without needing to write code. The platform's Actions system lets you build queries with filters, sorting options, and AND/OR logic directly within the builder. For example, you can create queries like "Filter Collection where property matches current user" and preview the results in real time.

One particularly helpful feature is the "Maximum number of items" setting, which ensures your app only fetches the data it needs—like the latest 10 products—instead of loading the entire collection. For larger datasets, enabling "Load Items as User Scrolls" under Advanced Options can make a big difference. In fact, this progressive loading feature reduced initial load times by 86% for lists containing 5,000 records.

When working with external data sources like Airtable or Xano, apply server-side filters and use pagination to limit data to 50 records per call. This approach can reduce load times by as much as 70%. By combining Adalo's tools with thoughtful query design, you can ensure your app runs smoothly, even with complex datasets.

Setting Up Pagination and Lazy Loading

What is Pagination and When to Use It

Pagination splits large datasets into smaller, more manageable sections, making it easier to load and display data. In Adalo, the Table component uses explicit pagination, featuring "Next" and "Previous" buttons to navigate through records.

Pagination is ideal for lists with over 20–50 items, such as product catalogs, user directories, or search results. For apps managing extensive datasets—think 10,000+ records—fetching data in smaller batches of 10–25 items per page can significantly improve performance. This approach reduces network requests and processing time by as much as 80–90%, allowing pages to load in under 2 seconds.

With Adalo's unlimited database storage on paid plans, you can build apps with extensive datasets without worrying about hitting record caps. The key is implementing proper pagination to ensure that data volume doesn't impact user experience.

Benefits of Lazy Loading

Lazy loading, known in Adalo as "Load Items as User Scrolls," delays loading content until it's needed. Instead of pulling all 5,000 items at once when a screen opens, the app initially loads just a small subset. As users scroll, additional items load progressively. This method can reduce initial load times by up to 86%.

Lazy loading offers more than just speed. It minimizes bandwidth usage by 50–70%, which is especially helpful for users on limited mobile data plans. It also reduces server load and prevents crashes when working with large datasets. For features like social feeds, image galleries, or long scrollable lists, lazy loading ensures a smoother experience by delivering content as needed.

How to Set Up Pagination and Lazy Loading in Adalo

Adalo makes it straightforward to implement both pagination and lazy loading, helping you optimize app performance and data handling.

• Enabling Lazy Loading: Choose a Simple, Custom, Image, or Card List, go to Advanced Options, and toggle on "Load Items as User Scrolls." This feature is enabled by default for new lists, but you'll need to activate it manually for older apps.
• Setting Up Pagination: Add a Table component to your screen and connect it to your database collection. In the component's sidebar, configure the "number of items per page" (10–20 records is a good starting point). The table will automatically generate "Next" and "Previous" navigation buttons. If you're using Adalo and Xano as a backend, make sure to enable paging in the GET API endpoints to support this feature.

For optimal performance, avoid nesting lists within other lists. Instead, stick to Adalo's native list components—like Simple, Card, or Image Lists—which are designed to work seamlessly with pagination and lazy loading.

Optimizing Images and Media Files

Compressing Images Without Losing Quality

Images often take up the largest chunk of your app's data usage. For instance, a single uncompressed 1MB photo can take about 0.4 seconds to download on a standard LTE connection. Now imagine a gallery of ten such photos—users would be stuck waiting 4 seconds for the screen to load.

The good news? Compression can solve this without compromising visual quality. Tools like compressor.io or Preview can shrink a 1MB file down to roughly 40KB, cutting load times for a ten-image gallery from 4 seconds to just 0.16 seconds. For iPhone users, tweaking quality settings can reduce a 6.7MB photo from an iPhone 16 Pro to as little as 2.1MB.

In March 2026, Adalo introduced an updated integration with Imgix, a real-time image processing tool that automatically optimizes uploaded images. This change, led by Jason Gilmore, resulted in a 33% improvement in compression across the platform. Internal tests revealed that a screen with five high-quality images saw load times drop from 6.32 seconds to just 1.15 seconds—a fivefold improvement. As Gilmore explained:

Our internal tests showed a 33% improvement in compression.

Once your images are compressed, selecting the right file format can further enhance performance.

Choosing the Right File Formats

Adalo supports popular formats like JPG and PNG, but modern apps can benefit from WebP, which provides better compression. Here's a quick breakdown:

• JPG: Best for photos where slight quality loss is acceptable.
• PNG: Ideal for graphics that need transparency or sharp edges.
• WebP: Typically 25–35% smaller than both JPG and PNG, making it a great choice for most use cases.

Adalo's Image property and File property support media types like JPG, PNG, and MP4, with a maximum file size of 50MB. For video, stick with the MP4 format and ensure files stay within this limit to maintain smooth playback across devices.

By combining the right file formats with compression, you can ensure efficient asset handling in Adalo.

Managing Assets in Adalo

Managing your app's assets effectively is just as important as optimizing data queries when it comes to reducing load times. Adalo offers several tools to help you streamline image and media handling.

Within Adalo's Builder, you can directly control image quality by appending ?q=30 to the end of any image URL. Lower quality values (like 20–30) result in smaller file sizes, while higher values (70–80) retain more detail. Experiment to find the balance that works best for your app's visuals.

For lists with multiple images, enable "Load Items as User Scrolls" in Advanced Options to avoid downloading all assets at once. Stick to Adalo's native list components—like Simple, Card, or Image Lists—as they're optimized for better performance with media-heavy content. Always compress images externally before uploading them; this simple step can reduce a typical photo from several megabytes to under 100KB.

Avoid hosting images on platforms like Google Drive, as they aren't optimized for app performance and may lead to broken links. Instead, upload your assets directly into Adalo's storage. This way, they'll automatically benefit from Imgix optimization and be delivered via Amazon CloudFront's CDN, which has brought average download times for components down to just 165.92 milliseconds.

Reducing API Calls and Using Caching

Optimizing API Call Frequency

Every API call introduces some delay, which can impact the user experience. To minimize this, focus on retrieving only the data you actually need. For example, in Adalo's External Collections, you can use filters like date ranges or user-specific conditions directly in the query. Instead of fetching all tasks in a task management app, you could filter for "status = active" and "user_id = current_user" right from the source.

Conditional logic is another way to cut down on unnecessary API calls. Before reaching out to the server, check if the data is already available locally. In Adalo's Visual Actions System, you can set up conditions like "if the user is logged in and the data is older than 5 minutes, then fetch from the API." This method can improve performance significantly, especially in high-traffic situations.

Avoid creating nested lists, as they can lead to an explosion of API calls. Instead, use Adalo's native list components—like Simple Lists, Card Lists, or Image Lists—and set a limit on the number of items fetched. For instance, you could configure the "Maximum number of items" field to retrieve only the 10 most recent records instead of pulling in hundreds.

Using Caching for Faster Load Times

Caching is a powerful way to speed up your app by storing frequently used data locally. This eliminates the need for repeated server calls and can reduce load times by as much as 70–90% for pages that users revisit.

In Adalo, caching can be enabled by setting expiration times on External Collections. For instance, you could cache user profile data for one hour, so it doesn't need to be fetched every time a screen is loaded. For static content, like product lists that rarely change, store the API responses in Adalo's internal database and update them only when the data changes.

Another smart caching technique is to store pre-calculated values. For example, instead of using a "Count" filter that calculates the total number of items on the fly, you can add a number property to your collection and update it whenever records are added or removed. This approach avoids recalculating the count every time a screen loads.

To keep cached data up-to-date, you can use time-based expiration (e.g., refreshing every 15 minutes) or event-based invalidation (e.g., clearing the cache after a user updates their information). For external services, webhooks from tools like Xano can trigger cache clears, ensuring your data stays accurate without constant polling.

Connecting External Databases with Adalo

Efficient caching pairs perfectly with external database integrations. Adalo supports seamless connections to external databases like Airtable, Xano, Google Sheets, MS SQL Server, and PostgreSQL through its External Collections feature. This eliminates the need for custom API development and allows optimized queries that fetch only the fields you need.

Take Airtable as an example. To reduce API calls, create filtered "Views" in Airtable that only return the records you need. For instance, a "Featured Products" view that shows only items marked as Featured will load much faster than pulling in thousands of records and filtering them within Adalo. Once your Airtable credentials are entered in Adalo's Builder, you can set up filters and configure caching (e.g., 30-minute intervals) to minimize unnecessary API requests.

It's also worth noting that Airtable has a limit of 5 requests per second per base. Exceeding this can cause slowdowns. For high-traffic data, consider storing a copy in Adalo's internal database to avoid hitting these limits. Additionally, use the PATCH method for record updates instead of PUT, as PATCH updates only the changed fields, reducing the amount of data being sent.

For those who prefer working with spreadsheets, Adalo's SheetBridge feature enables you to turn a Google Sheet into an actual database for the easiest control without database-related learning curves. This provides a familiar interface while still benefiting from Adalo's optimization capabilities.

Access to External Collections is available with Adalo's Professional plan or higher, starting at $65 per month. For apps with smaller datasets (under 5,000 records), Adalo's internal database can offer faster performance and near-zero API latency without the complexity of external connections.

Refactoring Data Structures for Better Performance

Flattening Complex Data Structures

Let's refine database structures to boost performance further, building on earlier query and collection optimizations.

Deeply nested data structures often lead to multiple database lookups for a single display, which slows things down. To fix this, consolidate frequently accessed data into fewer collections. This reduces the number of queries needed for each screen load, speeding up your app significantly.

Keep nesting levels to a maximum of four. Going beyond this can cause slower load times and unexpected behavior. If your data setup involves traversing several relationships, consider merging related collections. This not only streamlines queries but also helps your app respond faster and reduces battery usage on mobile devices.

With Adalo's 3.0 infrastructure running 3-4x faster than previous versions, well-structured data takes full advantage of these performance gains. The platform's modular architecture scales with your app's needs, meaning proper data structure becomes even more impactful as your user base grows.

With a flatter data structure, you can also introduce pre-calculated values to cut down processing time even further.

Storing Pre-Calculated Counts

Once your data is streamlined, pre-calculation becomes a powerful tool for improving performance by minimizing real-time computation.

Real-time calculations, like counting related records on the fly, put extra load on both the server and the user's device. For example, instead of dynamically counting comments on a post, store this value as a property in your collection.

"Creating counts with filters on a list record is similar to creating a list within a list, which will decrease your app's performance score."

To implement this, set up an action that updates the count property whenever a related record is added or removed. For instance, when a user submits a comment, trigger an update to increment the "Comment Count" property by 1. This way, your app can display counts instantly without relying on real-time calculations. It's a simple change that eliminates multiple simultaneous computations.

Adalo's testing shows that using pre-calculated counts can double an app's performance. And as your data scales, the benefits become even more noticeable. For instance, retrieving a pre-stored count for 10,000 records takes milliseconds, whereas a real-time count could take several seconds.

Setting Up Data Relationships in Adalo

After streamlining your data and introducing pre-calculations, the next step is to structure relationships for efficient querying.

Adalo's built-in relational database makes it easy to connect collections using custom formulas and AND/OR logic—all without writing code. However, the way you structure these relationships has a big impact on performance.

For one-to-many relationships (like users and their posts), store the parent ID in the child collection rather than using arrays in the parent. This setup allows for efficient filtering and supports pagination. For example, you can load a user's first 20 posts and fetch more only when needed.

For many-to-many relationships, use a junction collection instead of embedding arrays of related record IDs. For instance, instead of listing follower IDs in a User collection, create a "Follows" collection with fields for user_id and follower_id. This method avoids data duplication, keeps records lightweight, and speeds up queries—even in apps with thousands of relationships.

With the right data relationship setups, Adalo apps can scale beyond 1 million monthly active users. The platform's infrastructure scales alongside your needs, with no upper ceiling on growth.

If you're working with external databases like Airtable, Google Sheets, or PostgreSQL, optimize your data at the source. Use formulas and views to pre-filter and aggregate data server-side before it's sent to your app. This reduces the processing load on mobile devices and ensures smoother performance.

Monitoring and Testing Performance

Using Adalo's Performance Monitoring Tools

Adalo provides a performance score (ranging from 0 to 100) to help you measure and track data optimizations. This score is a great starting point for evaluating how your app's performance improves over time.

In the Adalo Editor, the Analytics tab is your go-to for monitoring key user engagement metrics like session duration, screen views, and interaction rates. For instance, if you notice a high drop-off rate on a specific screen—such as a product list—it could indicate performance issues like slow loading times. To dig deeper, you can integrate external analytics tools like Firebase through Zapier for more detailed insights.

For Progressive Web Apps (PWAs), tools like GTMetrix and Lighthouse offer objective performance metrics. Since iOS, Android, and PWAs can handle data differently, it's crucial to test your app across all target platforms to catch device-specific issues. Additionally, the Adalo Status Page can help you determine whether delays stem from your app or broader platform outages. This way, you can focus on fixing the right problems.

Adalo's upcoming X-Ray feature, part of the AI Builder suite due in early 2026, will identify performance issues before they affect users—proactively highlighting potential bottlenecks in your app's data handling.

Identifying Performance Bottlenecks

To identify bottlenecks, start by auditing your app for issues like screens with too many components, invisible elements still processing data, or deeply nested elements (beyond four levels). Use Adalo's preview mode during development to simulate load times on different devices. Compare these results with post-launch analytics to pinpoint screens where users drop off frequently.

Common performance culprits include unpaginated lists, heavy real-time calculations, and slow database queries. For example, lists with more than 100 records can push load times beyond three seconds. Comparing the speed of external collections versus Adalo's internal database can also reveal areas for improvement.

Browser developer tools are another useful resource for spotting slow API calls. Additionally, ensure that images are compressed to reduce load times. As David Adkin, Adalo's founder, emphasizes:

Adalo apps need to perform just as well as apps built with code, and they each need to do that even when they are used by hundreds of thousands and even millions of people!

The Adalo 3.0 infrastructure overhaul delivered on this vision, with apps now running 3-4x faster and modular infrastructure that scales with demand. Most third-party performance ratings and comparisons predate this major update, so current real-world performance often exceeds what older reviews suggest.

Testing and Continuous Optimization

Once you've identified performance bottlenecks, it's time to test and refine your optimizations. For example, after implementing manual pagination or caching, run A/B tests to compare the new performance against your baseline. Adalo's instant update feature allows you to roll out changes across platforms quickly, so you can monitor analytics and ensure your updates are effective.

Keep an eye on post-deployment analytics to catch any regressions and maintain load times under three seconds. It's also a good idea to test your app under different network conditions. An app that performs well on Wi-Fi might struggle on slower LTE connections, especially for users located far from Adalo's US-based servers. Regular testing ensures your app stays fast and reliable no matter the circumstances.

With Adalo's paid plans now including unlimited usage—no App Actions charges or usage-based billing—you can test and iterate without worrying about unexpected costs. This removes a common barrier to thorough performance testing and optimization.

How Adalo Compares for Performance Optimization

When choosing a platform for building performance-optimized apps, the underlying architecture matters significantly. Here's how Adalo's approach compares to other popular options:

Platform	Starting Price	Database Limits	Native Mobile Apps	Usage Charges
Adalo	$36/month	Unlimited records	Yes (iOS & Android)	None
Bubble	$59/month	Limited by Workload Units	Web wrapper only	Yes (Workload Units)
Glide	$60/month	Row limits apply	No App Store publishing	Yes (data rows)
FlutterFlow	$70/month/user	External DB required	Yes	Varies by DB

Bubble offers extensive customization options, but this flexibility often results in slower applications that struggle under increased load. Bubble's mobile app solution is a wrapper for the web app, which can introduce performance challenges at scale. One app version doesn't automatically update web, Android, and iOS apps deployed to their respective stores. Bubble's Workload Units create unpredictable billing that makes cost planning difficult, and many users report needing to hire experts to achieve acceptable performance at scale.

FlutterFlow is a low-code (not no-code) platform designed for technical users. Users must set up and manage their own external database, which requires significant learning and can create scalability problems if not configured optimally. The ecosystem is rich with consultants precisely because so many users need help—often spending significant sums chasing scalability. FlutterFlow's builder also limits your view to 2 screens at once, whereas Adalo can display up to 400 screens on one canvas for faster navigation.

Glide excels at spreadsheet-based apps with its template-focused approach, enabling fast building and publishing. However, this creates generic, simplistic apps with limited creative freedom. Glide doesn't support Apple App Store or Google Play Store publishing, and charges for data row overages.

Adalo's purpose-built architecture maintains performance at scale, with over 3 million apps created on the platform. The visual builder has been described as "easy as PowerPoint," while the upcoming AI Builder promises vibe-coding creation speed for those who prefer natural language app development.

Conclusion

Summary of Optimization Strategies

Optimizing your app's performance is a continuous process that directly impacts user retention. This guide has covered essential strategies, including organizing data collections effectively, crafting optimized queries, using pagination and lazy loading, compressing images, reducing redundant API calls through caching, and simplifying data structures by flattening complexity or storing pre-calculated counts.

These methods work together to minimize the data your app needs to transfer, process, and display. For example, progressive loading can slash initial load times by up to 86%, while compressing images before uploading significantly reduces file sizes without compromising visual quality. Similarly, caching frequently accessed data instead of making repetitive API calls can improve performance by 40-60%. Altogether, these optimizations can reduce load times by 2-5x, helping you stay under the critical 3-second threshold—a key factor in whether 53% of mobile users stick around or move on.

Next Steps for Adalo Users

To put these strategies into action, start by reviewing your app's current setup. Use Adalo's database builder to audit your data collections and enable features like "Load Items as User Scrolls" to improve efficiency. Compress media files before uploading them and configure caching for frequently used queries. During development, take advantage of Adalo's preview mode to test your app's load times across various devices and network speeds.

Adalo's tools make these optimizations straightforward, even for non-coders. The platform's visual query tools, built-in database management, and instant cross-platform updates let you implement features like pagination, restructure data, and monitor performance—all without touching a single line of code. Additionally, Adalo's marketplace offers performance-optimized templates, making it easier for new users to build scalable apps.

With the Adalo 3.0 infrastructure delivering 3-4x faster performance, no record limits on paid plans, and no usage-based charges, the platform provides a solid foundation for high-performing apps. Once these initial optimizations are in place, regular testing and monitoring are crucial to maintaining sub-3-second load times across all devices.

Making Faster Web Apps - Easy Perf Wins

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FAQ

Question	Answer
Why choose Adalo over other app building solutions?	Adalo is an AI-powered app builder that creates true native iOS and Android apps. Unlike web wrappers, it compiles to native code and publishes directly to both the Apple App Store and Google Play Store from a single codebase—the hardest part of launching an app handled automatically. With unlimited database records on paid plans and no usage-based charges, you can scale without surprise bills.
What's the fastest way to build and publish an app to the App Store?	Adalo's drag-and-drop interface and AI-assisted building let you go from idea to published app in days rather than months. The platform handles the complex App Store submission process, so you can focus on your app's features and user experience instead of wrestling with certificates, provisioning profiles, and store guidelines.
How can I reduce my app's load time below 3 seconds?	Implement a combination of strategies: enable pagination and lazy loading for lists with over 20-50 items, compress images before uploading, use server-side filtering instead of client-side, and cache frequently accessed data. Adalo's built-in tools make these optimizations straightforward, and together they can reduce load times by 2-5x.
What causes slow app performance and how do I fix it?	Common performance culprits include unpaginated lists loading thousands of records, uncompressed images, nested lists causing multiple API calls, and real-time calculations running on every screen load. Fix these by limiting records fetched to 10-50 items per page, compressing images to under 100KB, avoiding nested list components, and storing pre-calculated counts instead of computing them dynamically.
Should I use Adalo's internal database or connect an external database like Airtable or Xano?	For apps with smaller datasets under 5,000 records, Adalo's internal database offers faster performance with near-zero API latency. For larger datasets or complex data requirements, external databases like Airtable or Xano work well when properly optimized with server-side filters and pagination. External Collections require Adalo's Professional plan ($65/month) and benefit from caching to minimize API calls.
How do I optimize images in my Adalo app?	Compress images before uploading using tools like compressor.io to reduce file sizes from megabytes to under 100KB. Adalo automatically optimizes uploaded images through Imgix integration, which improved compression by 33% platform-wide. Use WebP format when possible for 25-35% smaller files than JPG or PNG, and enable "Load Items as User Scrolls" for image galleries to avoid downloading all assets at once.
Which is more affordable, Adalo or Bubble?	Adalo starts at $36/month with unlimited usage and no record limits on paid plans. Bubble starts at $59/month but includes Workload Units that create unpredictable usage-based charges, plus record limits that can restrict growth. For predictable pricing and native mobile app publishing, Adalo offers better value.
Is Adalo better than Bubble for mobile apps?	For native mobile apps, yes. Adalo compiles to true native iOS and Android code, while Bubble's mobile solution is a web wrapper. Native apps perform better, especially under load, and provide a smoother user experience. Bubble offers more web customization, but often requires hiring experts to achieve acceptable mobile performance at scale.
How long does it take to build a performance-optimized app?	With Adalo's visual builder and optimization features built-in, you can build and optimize a database-driven app in days rather than months. Implementing pagination, lazy loading, and caching takes minutes using Adalo's toggle settings and configuration options—no coding required.
Do I need coding experience to optimize my app's performance?	No. Adalo's visual tools let you implement advanced optimizations like pagination, lazy loading, query filters, and caching without writing code. Features like "Load Items as User Scrolls" can reduce initial load times by up to 86% with a single toggle. The platform handles the technical complexity behind the scenes.