Adalo Best No-Code Platforms: The Honest Truth

// adalo-collection-sync.js
// Syncs Adalo "Users" collection to PostgreSQL with rate limit handling
// Requires: adalo-api-sdk@2.3.1, pg@8.11.3, dotenv@16.3.1
import { AdaloClient } from 'adalo-api-sdk';
import { Pool } from 'pg';
import dotenv from 'dotenv';
import pino from 'pino';

dotenv.config();

// Initialize Adalo client with API key and app ID
const adaloClient = new AdaloClient({
  apiKey: process.env.ADALO_API_KEY,
  appId: process.env.ADALO_APP_ID,
  // Set timeout to 10s to avoid hanging requests
  timeout: 10000,
});

// Initialize PostgreSQL connection pool
const pgPool = new Pool({
  host: process.env.PG_HOST,
  port: process.env.PG_PORT,
  database: process.env.PG_DB,
  user: process.env.PG_USER,
  password: process.env.PG_PASSWORD,
  max: 10, // Max 10 concurrent connections
});

// Initialize structured logger
const logger = pino({
  level: process.env.LOG_LEVEL || 'info',
  transport: {
    target: 'pino-pretty',
  },
});

// Retry logic for Adalo API rate limits (429 errors)
async function retryOnRateLimit(fn, maxRetries = 3, baseDelayMs = 1000) {
  let attempt = 0;
  while (attempt < maxRetries) {
    try {
      return await fn();
    } catch (error) {
      if (error.status === 429 && attempt < maxRetries - 1) {
        const delay = baseDelayMs * Math.pow(2, attempt); // Exponential backoff
        logger.warn(`Rate limited. Retrying in ${delay}ms. Attempt ${attempt + 1}/${maxRetries}`);
        await new Promise(resolve => setTimeout(resolve, delay));
        attempt++;
      } else {
        throw error; // Rethrow non-429 errors or max retries exceeded
      }
    }
  }
}

// Fetch all records from Adalo "Users" collection with pagination
async function fetchAllAdaloUsers() {
  let allUsers = [];
  let offset = 0;
  const limit = 100; // Adalo max pagination limit per request

  while (true) {
    const fetchPage = async () => {
      const response = await adaloClient.collections.getRecords({
        collectionId: 'users', // Adalo collection ID for Users
        offset,
        limit,
      });
      return response;
    };

    const page = await retryOnRateLimit(fetchPage);
    allUsers = allUsers.concat(page.records);

    // Break if no more pages
    if (page.records.length < limit) break;
    offset += limit;
    logger.info(`Fetched ${allUsers.length} total users so far`);
  }

  return allUsers;
}

// Upsert users into PostgreSQL
async function syncUsersToPG(users) {
  const client = await pgPool.connect();
  try {
    await client.query('BEGIN');

    // Create temp table for bulk upsert
    await client.query(`
      CREATE TEMP TABLE tmp_users (
        adalo_id VARCHAR(255) PRIMARY KEY,
        email VARCHAR(255) UNIQUE NOT NULL,
        full_name VARCHAR(255),
        created_at TIMESTAMP,
        last_active TIMESTAMP
      ) ON COMMIT DROP;
    `);

    // Insert into temp table
    const insertQuery = `
      INSERT INTO tmp_users (adalo_id, email, full_name, created_at, last_active)
      VALUES ($1, $2, $3, $4, $5)
    `;
    for (const user of users) {
      await client.query(insertQuery, [
        user.id,
        user.Email, // Adalo field name
        user['Full Name'] || null,
        user['Created At'] ? new Date(user['Created At']) : null,
        user['Last Active'] ? new Date(user['Last Active']) : null,
      ]);
    }

    // Upsert from temp to main users table
    await client.query(`
      INSERT INTO users (adalo_id, email, full_name, created_at, last_active)
      SELECT adalo_id, email, full_name, created_at, last_active FROM tmp_users
      ON CONFLICT (adalo_id) DO UPDATE SET
        email = EXCLUDED.email,
        full_name = EXCLUDED.full_name,
        last_active = EXCLUDED.last_active;
    `);

    await client.query('COMMIT');
    logger.info(`Synced ${users.length} users to PostgreSQL`);
  } catch (error) {
    await client.query('ROLLBACK');
    logger.error({ error }, 'Failed to sync users to PostgreSQL');
    throw error;
  } finally {
    client.release();
  }
}

// Main execution
async function main() {
  try {
    logger.info('Starting Adalo -> PostgreSQL user sync');
    const users = await fetchAllAdaloUsers();
    logger.info(`Fetched ${users.length} total users from Adalo`);
    await syncUsersToPG(users);
    logger.info('Sync completed successfully');
  } catch (error) {
    logger.error({ error }, 'Sync failed');
    process.exit(1);
  } finally {
    await pgPool.end();
  }
}

// Run main if script is executed directly
if (import.meta.url === `file://${process.argv[1]}`) {
  main();
}

// AdaloCustomCarousel.jsx
// Custom React Native carousel component for Adalo 2.14.0+
// Compatible with Adalo's custom component API: https://help.adalo.com/custom-components
// Requires: react-native@0.72.0, react@18.2.0, react-native-snap-carousel@3.9.1

import React, { useState, useCallback, useEffect } from 'react';
import { View, Image, StyleSheet, ActivityIndicator, Text } from 'react-native';
import Carousel from 'react-native-snap-carousel';
import PropTypes from 'prop-types';

// Error boundary to catch rendering errors in Adalo
class CarouselErrorBoundary extends React.Component {
  constructor(props) {
    super(props);
    this.state = { hasError: false, error: null };
  }

  static getDerivedStateFromError(error) {
    return { hasError: true, error };
  }

  componentDidCatch(error, errorInfo) {
    console.error('Carousel component crashed:', error, errorInfo);
    // Log to Adalo's custom component error reporting if available
    if (window?.Adalo?.logError) {
      window.Adalo.logError({
        component: 'CustomCarousel',
        error: error.message,
        stack: errorInfo.componentStack,
      });
    }
  }

  render() {
    if (this.state.hasError) {
      return (

          Failed to load carousel
          {this.state.error?.message || 'Unknown error'}

      );
    }

    return this.props.children;
  }
}

// Main carousel component
const AdaloCustomCarousel = ({ 
  images, 
  autoplay = true, 
  autoplayInterval = 3000, 
  itemWidth = 300, 
  sliderWidth = 350,
  onImagePress,
  loadingIndicatorColor = '#007AFF',
}) => {
  const [activeIndex, setActiveIndex] = useState(0);
  const [imagesLoaded, setImagesLoaded] = useState(0);
  const [loadError, setLoadError] = useState(false);

  // Validate images prop on mount
  useEffect(() => {
    if (!Array.isArray(images)) {
      console.error('AdaloCustomCarousel: images prop must be an array of URLs');
      setLoadError(true);
      return;
    }
    if (images.length === 0) {
      console.warn('AdaloCustomCarousel: No images provided to carousel');
    }
  }, [images]);

  // Track image load progress
  const handleImageLoad = useCallback(() => {
    setImagesLoaded(prev => prev + 1);
  }, []);

  // Handle image load error
  const handleImageError = useCallback((error, index) => {
    console.error(`Failed to load carousel image at index ${index}:`, error);
    // Fallback to placeholder if image fails to load
    images[index] = 'https://via.placeholder.com/300x200?text=Image+Not+Found';
  }, [images]);

  // Render individual carousel item
  const renderCarouselItem = useCallback(({ item, index }) => {
    return (

         handleImageError(e.nativeEvent.error, index)}
        />

    );
  }, [handleImageLoad, handleImageError]);

  // Handle carousel snap (Adalo event logging)
  const handleSnapToItem = useCallback((index) => {
    setActiveIndex(index);
    // Log event to Adalo analytics if available
    if (window?.Adalo?.logEvent) {
      window.Adalo.logEvent('carousel_snap', {
        component: 'CustomCarousel',
        activeIndex: index,
        totalItems: images.length,
      });
    }
    if (onImagePress) {
      onImagePress(item, index);
    }
  }, [images, onImagePress]);

  if (loadError) {
    return (

        Invalid images configuration

    );
  }

  if (images.length === 0) {
    return (

        No images to display

    );
  }

  return (


        {imagesLoaded < images.length && (

        )}


          {images.map((_, index) => (

          ))}



  );
};

// PropTypes for Adalo component prop validation
AdaloCustomCarousel.propTypes = {
  images: PropTypes.arrayOf(PropTypes.string).isRequired,
  autoplay: PropTypes.bool,
  autoplayInterval: PropTypes.number,
  itemWidth: PropTypes.number,
  sliderWidth: PropTypes.number,
  onImagePress: PropTypes.func,
  loadingIndicatorColor: PropTypes.string,
};

// Default props
AdaloCustomCarousel.defaultProps = {
  autoplay: true,
  autoplayInterval: 3000,
  itemWidth: 300,
  sliderWidth: 350,
  loadingIndicatorColor: '#007AFF',
};

const styles = StyleSheet.create({
  container: {
    position: 'relative',
  },
  carouselItem: {
    borderRadius: 8,
    overflow: 'hidden',
  },
  carouselImage: {
    width: '100%',
    height: 200,
    borderRadius: 8,
  },
  loadingIndicator: {
    position: 'absolute',
    top: '50%',
    left: '50%',
    zIndex: 10,
    transform: [{ translateX: -25 }, { translateY: -25 }],
  },
  pagination: {
    flexDirection: 'row',
    justifyContent: 'center',
    marginTop: 10,
  },
  paginationDot: {
    width: 8,
    height: 8,
    borderRadius: 4,
    backgroundColor: '#C7C7CC',
    marginHorizontal: 4,
  },
  paginationDotActive: {
    backgroundColor: '#007AFF',
  },
  errorContainer: {
    padding: 20,
    backgroundColor: '#FFF0F0',
    borderRadius: 8,
    alignItems: 'center',
  },
  errorText: {
    color: '#FF3B30',
    fontSize: 16,
    fontWeight: '600',
  },
  errorSubtext: {
    color: '#FF3B30',
    fontSize: 12,
    marginTop: 4,
  },
  emptyContainer: {
    padding: 20,
    backgroundColor: '#F2F2F7',
    borderRadius: 8,
    alignItems: 'center',
  },
  emptyText: {
    color: '#8E8E93',
    fontSize: 16,
  },
});

export default AdaloCustomCarousel;

# no-code-benchmark.py
# Benchmarks Adalo vs Bubble vs FlutterFlow across 4 key dev metrics
# Requires: requests==2.31.0, pandas==2.1.4, matplotlib==3.8.2, python-dotenv==1.0.0
import os
import time
import requests
import pandas as pd
import matplotlib.pyplot as plt
from dotenv import load_dotenv
from typing import Dict, List

load_dotenv()

# Configuration for each platform
PLATFORMS = {
    'adalo': {
        'api_base': 'https://api.adalo.com/v0',
        'app_id': os.getenv('ADALO_BENCH_APP_ID'),
        'api_key': os.getenv('ADALO_BENCH_API_KEY'),
        'build_endpoint': '/builds',
        'collection_endpoint': '/collections/users/records',
        'pricing_per_mau': 0.12, # $0.12 per MAU over 1k
    },
    'bubble': {
        'api_base': 'https://api.bubble.io/1.1',
        'app_id': os.getenv('BUBBLE_BENCH_APP_ID'),
        'api_key': os.getenv('BUBBLE_BENCH_API_KEY'),
        'build_endpoint': '/obj/build',
        'collection_endpoint': '/obj/user',
        'pricing_per_mau': 0.04, # $0.04 per MAU over 1k
    },
    'flutterflow': {
        'api_base': 'https://api.flutterflow.io/v1',
        'app_id': os.getenv('FLUTTERFLOW_BENCH_APP_ID'),
        'api_key': os.getenv('FLUTTERFLOW_BENCH_API_KEY'),
        'build_endpoint': '/builds',
        'collection_endpoint': '/firestore/users',
        'pricing_per_mau': 0.08, # $0.08 per MAU over 1k
    }
}

# Metrics to collect
METRICS = [
    'api_avg_response_ms',
    'api_p99_response_ms',
    'build_time_sec',
    'cost_per_10k_mau_usd',
    'max_api_requests_per_day',
]

def get_auth_headers(platform: str) -> Dict[str, str]:
    """Generate auth headers for each platform's API"""
    config = PLATFORMS[platform]
    if platform == 'adalo':
        return {
            'Authorization': f'Bearer {config["api_key"]}',
            'X-Adalo-App-Id': config['app_id'],
            'Content-Type': 'application/json',
        }
    elif platform == 'bubble':
        return {
            'Authorization': f'Bearer {config["api_key"]}',
            'Content-Type': 'application/json',
        }
    elif platform == 'flutterflow':
        return {
            'X-FlutterFlow-API-Key': config['api_key'],
            'X-FlutterFlow-App-Id': config['app_id'],
            'Content-Type': 'application/json',
        }
    raise ValueError(f'Unsupported platform: {platform}')

def benchmark_api_response(platform: str, num_requests: int = 100) -> Dict[str, float]:
    """Measure API response times for 100 GET requests to user collection"""
    config = PLATFORMS[platform]
    headers = get_auth_headers(platform)
    endpoint = f'{config["api_base"]}{config["collection_endpoint"]}'
    response_times = []

    for i in range(num_requests):
        try:
            start = time.perf_counter()
            response = requests.get(
                endpoint,
                headers=headers,
                params={'limit': 10},
                timeout=10,
            )
            end = time.perf_counter()
            if response.status_code == 200:
                response_times.append((end - start) * 1000) # Convert to ms
            else:
                print(f'Request {i} to {platform} failed: {response.status_code}')
        except requests.exceptions.RequestException as e:
            print(f'Request {i} to {platform} errored: {e}')

    if not response_times:
        return {'api_avg_response_ms': 0, 'api_p99_response_ms': 0}

    response_times.sort()
    avg = sum(response_times) / len(response_times)
    p99_index = int(len(response_times) * 0.99)
    p99 = response_times[p99_index]

    return {
        'api_avg_response_ms': round(avg, 2),
        'api_p99_response_ms': round(p99, 2),
    }

def benchmark_build_time(platform: str) -> float:
    """Trigger a test build and measure time to completion"""
    config = PLATFORMS[platform]
    headers = get_auth_headers(platform)
    endpoint = f'{config["api_base"]}{config["build_endpoint"]}'

    try:
        # Trigger build
        start = time.perf_counter()
        response = requests.post(
            endpoint,
            headers=headers,
            json={'platform': 'ios', 'config': 'release'},
            timeout=30,
        )
        if response.status_code not in (200, 201):
            print(f'Failed to trigger build for {platform}: {response.status_code}')
            return 0.0

        build_id = response.json().get('id')
        if not build_id:
            print(f'No build ID returned for {platform}')
            return 0.0

        # Poll for build completion (max 10 minutes)
        max_polls = 60
        poll_interval = 10
        for _ in range(max_polls):
            status_response = requests.get(
                f'{endpoint}/{build_id}',
                headers=headers,
                timeout=10,
            )
            if status_response.status_code == 200:
                status = status_response.json().get('status')
                if status == 'completed':
                    end = time.perf_counter()
                    return round(end - start, 2)
                elif status == 'failed':
                    print(f'Build failed for {platform}')
                    return 0.0
            time.sleep(poll_interval)
        print(f'Build timed out for {platform}')
        return 0.0
    except requests.exceptions.RequestException as e:
        print(f'Build benchmark failed for {platform}: {e}')
        return 0.0

def calculate_cost(platform: str, mau: int = 10000) -> float:
    """Calculate cost for given MAU count (over 1k free tier)"""
    config = PLATFORMS[platform]
    billable_mau = max(0, mau - 1000)
    return round(billable_mau * config['pricing_per_mau'], 2)

def run_full_benchmark() -> pd.DataFrame:
    """Run all benchmarks and return results as DataFrame"""
    results = []

    for platform in PLATFORMS.keys():
        print(f'Benchmarking {platform}...')
        result = {'platform': platform}

        # API response benchmark
        api_metrics = benchmark_api_response(platform)
        result.update(api_metrics)

        # Build time benchmark
        build_time = benchmark_build_time(platform)
        result['build_time_sec'] = build_time

        # Cost calculation
        result['cost_per_10k_mau_usd'] = calculate_cost(platform, 10000)

        # API limit (from docs)
        result['max_api_requests_per_day'] = {
            'adalo': 10000,
            'bubble': 50000,
            'flutterflow': 30000,
        }[platform]

        results.append(result)
        print(f'Completed {platform} benchmark')

    return pd.DataFrame(results)

def plot_results(df: pd.DataFrame):
    """Generate bar charts for each metric"""
    for metric in METRICS:
        plt.figure(figsize=(10, 6))
        plt.bar(df['platform'], df[metric])
        plt.title(f'{metric.replace("_", " ").title()} by Platform')
        plt.ylabel(metric.replace("_", " ").title())
        plt.xlabel('Platform')
        plt.grid(axis='y', linestyle='--', alpha=0.7)
        plt.savefig(f'benchmark_{metric}.png')
        plt.close()
    print('Saved benchmark charts to current directory')

if __name__ == '__main__':
    # Run benchmarks
    benchmark_df = run_full_benchmark()

    # Save results to CSV
    benchmark_df.to_csv('no_code_benchmark_results.csv', index=False)
    print('Saved benchmark results to no_code_benchmark_results.csv')

    # Print summary
    print('\nBenchmark Summary:')
    print(benchmark_df.to_string(index=False))

    # Generate plots
    plot_results(benchmark_df)

// Short snippet: Retry wrapper for Adalo API calls
async function retryAdaloCall(fn, maxRetries = 3) {
  for (let i = 0; i < maxRetries; i++) {
    try {
      return await fn();
    } catch (error) {
      if (error.status === 429 && i < maxRetries - 1) {
        await new Promise(r => setTimeout(r, 1000 * Math.pow(2, i)));
        continue;
      }
      throw error;
    }
  }
}

// Short snippet: Custom component prop validation
AdaloCustomCarousel.propTypes = {
  images: PropTypes.arrayOf(PropTypes.string).isRequired,
  autoplay: PropTypes.bool,
  onImagePress: PropTypes.func,
};

// Short snippet: Run benchmark for Adalo only
benchmark_df = run_full_benchmark()
adalo_metrics = benchmark_df[benchmark_df['platform'] == 'adalo']
print(adalo_metrics.to_string())