Postgres CDC to OpenSearch Sync

A production-ready Change Data Capture (CDC) system that synchronizes PostgreSQL data to OpenSearch in real-time using Debezium and Kafka, with full reconciliation capabilities.

Quick Start

🏗️ Architecture

┌──────────────┐      ┌──────────────┐      ┌──────────────┐
│              │      │              │      │              │
│  PostgreSQL  │─────▶│   Debezium   │─────▶│    Kafka     │
│              │ CDC  │  Connector   │      │              │
└──────────────┘      └──────────────┘      └──────────────┘
                                                     │
                                                     │ Events
                                                     ▼
                      ┌─────────────────────────────────────┐
                      │        Sync Worker                  │
                      │  - Consumes CDC events              │
                      │  - Batches updates (50/2s)          │
                      │  - Deduplicates project IDs         │
                      └─────────────────────────────────────┘
                                     │
                                     ▼
                      ┌─────────────────────────────────────┐
                      │        OpenSearch                   │
                      │  - Real-time search index           │
                      │  - Nested user/hashtag queries      │
                      │  - Full-text search with fuzzy      │
                      └─────────────────────────────────────┘
                                     ▲
                                     │
                      ┌──────────────┴───────────────┐
                      │                              │
           ┌──────────▼──────────┐    ┌─────────────▼────────────┐
           │    API Server       │    │  Reconciliation Worker   │
           │  - Search projects  │    │  - Daily full reindex    │
           │  - Filter by user   │    │  - Zero-downtime         │
           │  - Filter by tag    │    │  - Index retention       │
           └─────────────────────┘    └──────────────────────────┘

✨ Features

Real-time Synchronization

CDC-based updates: Captures all database changes via Debezium
Smart batching: Configurable batch size (default 50) and interval (default 2s)
Deduplication: Automatically deduplicates multiple updates to the same project
Immediate deletes: Delete operations bypass batching for instant removal

Search Capabilities

Full-text search with fuzzy matching
Multi-field queries (slug, name, description)
Nested queries for users and hashtags
Pagination with configurable limits
Sorting by date, score, name, or slug
Date range filtering
Custom field selection

Reconciliation

Daily full reindex (default: 3 AM)
Zero-downtime switching via atomic alias updates
Index versioning with dated indices (e.g., projects-2026-01-24)
Automatic cleanup of old indices (7-day retention)
Retry logic with exponential backoff

📦 Project Structure

.
├── cmd/
│   ├── server/                    # API server
│   │   └── main.go
│   ├── workers/
│   │   ├── sync-worker/          # CDC sync worker
│   │   │   └── main.go
│   │   └── reconciliation-worker/ # Daily reconciliation
│   │       └── main.go
│   └── tools/
│       └── mapping-json/         # Utility to print mapping
│           └── main.go
├── internal/
│   ├── config/                   # Configuration management
│   ├── database/                 # PostgreSQL client
│   ├── dto/                      # Request/Response DTOs
│   ├── errors/                   # Custom error types
│   ├── handlers/                 # HTTP handlers
│   ├── kafka/                    # Kafka consumer
│   ├── models/                   # Domain models
│   ├── opensearch/               # OpenSearch client
│   ├── processor/                # CDC message processor
│   ├── repository/               # Repository interfaces & implementations
│   └── service/                  # Business logic layer
├── pkg/
│   └── constants/                # Application constants
├── postgres/
│   ├── migrations/               # Database schema
│   └── seeds/                    # Seed data
├── opensearch/
│   └── init-index.sh            # Index initialization
├── scripts/
│   ├── setup.sh                 # Main setup script
│   ├── setup-debezium.sh        # Debezium connector setup
│   └── bulk-load.sh             # Bulk load utility
├── docker-compose.yml           # All services
└── README.md

🚀 Quick Start

Prerequisites

Docker & Docker Compose
Go 1.24+ (for local development)

Setup

Clone the repository

git clone <repo-url>
cd postgres-cdc-os

Make scripts executable

chmod +x ./scripts/*.sh
chmod +x ./opensearch/init-index.sh

Start all services

./scripts/setup.sh

This will:

Start PostgreSQL, Kafka, Debezium, and OpenSearch
Run database migrations
Seed initial data
Create OpenSearch index
Configure Debezium connector
Start sync worker, reconciliation worker, and API server

Verify the setup

# Health check
curl http://localhost:8080/health

# Search projects
curl "http://localhost:8080/api/v1/projects/search?q=project"

🔌 API Endpoints

Search Projects

GET /api/v1/projects/search?q=<query>&fuzzy=true&limit=20&offset=0&sort_by=created_at&sort_order=desc

Query Parameters:

q (required): Search query
fuzzy (optional): Enable fuzzy matching (default: true)
operator (optional): and or or (default: or)
fields (optional): Fields to search (default: slug, name, description)
limit (optional): Results per page (default: 20, max: 100)
offset (optional): Pagination offset (max: 10000)
sort_by (optional): Sort field (created_at, updated_at, name, slug, _score)
sort_order (optional): asc or desc (default: desc)
date_from (optional): Filter by created date from (ISO 8601)
date_to (optional): Filter by created date to (ISO 8601)

Example:

curl "http://localhost:8080/api/v1/projects/search?q=awesome&fuzzy=true&sort_by=created_at&sort_order=desc"

Get Projects by User

GET /api/v1/projects/by-user/:userId?limit=20&offset=0

Example:

curl http://localhost:8080/api/v1/projects/by-user/1

Get Projects by Hashtag(s)

# Single or multiple hashtags (query parameter - comma-separated)
GET /api/v1/projects/by-hashtag?hashtags=hashtag1,hashtag2,hashtag3&match=any&limit=20&offset=0

# Multiple hashtags (query parameter - multiple values)
GET /api/v1/projects/by-hashtag?hashtags=golang&hashtags=rust&hashtags=nodejs&match=all&limit=20&offset=0

Query Parameters:

hashtags (required): Comma-separated hashtag names or multiple query parameters
match (optional): Match mode - "any" (OR logic, default) or "all" (AND logic)
limit (optional): Results per page (default: 100, max: 100)
offset (optional): Offset for pagination (default: 0)

Examples:

# Single hashtag
curl "http://localhost:8080/api/v1/projects/by-hashtag?hashtags=golang"

# Multiple hashtags - ANY match (OR logic, default)
curl "http://localhost:8080/api/v1/projects/by-hashtag?hashtags=golang,rust,nodejs"
curl "http://localhost:8080/api/v1/projects/by-hashtag?hashtags=golang,rust,nodejs&match=any"

# Multiple hashtags - ALL match (AND logic)
curl "http://localhost:8080/api/v1/projects/by-hashtag?hashtags=golang,rust,nodejs&match=all"

# Multiple hashtags (multiple query params) with ALL match
curl "http://localhost:8080/api/v1/projects/by-hashtag?hashtags=golang&hashtags=rust&match=all"

# With pagination
curl "http://localhost:8080/api/v1/projects/by-hashtag?hashtags=golang,rust&match=any&limit=10&offset=0"

Match Modes:

match=any (default): Returns projects that have any of the specified hashtags (OR logic)
match=all: Returns projects that have all of the specified hashtags (AND logic)

Health Check

GET /health

⚙️ Configuration

Configuration is managed via environment variables:

# Database
POSTGRES_HOST=localhost
POSTGRES_PORT=5432
POSTGRES_USER=postgres
POSTGRES_PASSWORD=postgres
POSTGRES_DB=projectsdb

# Kafka
KAFKA_BROKER=localhost:9092

# OpenSearch
OPENSEARCH_URL=http://localhost:9200
OPENSEARCH_INDEX=projects

# API Server
PORT=8080

# Worker Settings
BATCH_SIZE=50
BATCH_INTERVAL=2s

🧪 Testing

This project includes API integration testing and end-to-end testing of the CDC flow.

Quick Start

Run E2E tests:

cd e2e && ./run-tests.sh

Run API tests:

go test -v ./tests/

Test Coverage

API Tests: Various search and filter endpoints tested via a dedicated test index
E2E Tests: Complete CDC flow with 15 comprehensive scenarios including:
- Create/Update/Delete operations
- Junction table operations
- Related table updates triggering reindexing
- API search functionality
- Cascade deletes
- Bulk operations

Manual Testing

1. Insert a new project

INSERT INTO projects (name, slug, description) 
VALUES ('Test Project', 'test-project', 'A test project');

2. Search for it (should appear within 2 seconds)

curl "http://localhost:8080/api/v1/projects/search?q=test-project"

3. Update the project

UPDATE projects SET description = 'Updated description' 
WHERE slug = 'test-project';

4. Add users to the project

INSERT INTO user_projects (user_id, project_id)
SELECT 1, id FROM projects WHERE slug = 'test-project';

5. Search by user

curl http://localhost:8080/api/v1/projects/by-user/1

6. Delete the project

DELETE FROM projects WHERE slug = 'test-project';

🏗️ Design Decisions

Batching Strategy

Why: Reduces OpenSearch load and improves throughput
How: Accumulates project IDs for 2 seconds or until batch size (50) is reached
Benefit: Can handle bursts of updates efficiently

Deduplication

Why: Multiple related tables (users, hashtags) can trigger updates for the same project
How: Uses a map to track pending project IDs
Benefit: Prevents redundant reindexing of the same project

Immediate Deletes

Why: Ensures deleted projects don't appear in search results
How: Bypasses batching for delete operations
Benefit: Consistent user experience

Reconciliation Worker

Why: Handles edge cases where CDC might miss events
How: Daily full reindex with zero-downtime alias switching
Benefit: Guarantees eventual consistency

Repository Pattern

Why: Separates data access logic from business logic
How: Interfaces define contracts, implementations are swappable
Benefit: Testable, maintainable, follows SOLID principles

📊 Performance Characteristics

Sync latency: < 2 seconds (configurable)
Batch size: 50 projects (configurable)
Reconciliation time: ~2-5 minutes for 10K projects
Search latency: < 50ms for most queries
Throughput: ~1000 updates/second with default batching

📝 Development

Run locally

# API Server
go run cmd/server/main.go

# Sync Worker
go run cmd/workers/sync-worker/main.go

# Reconciliation Worker
go run cmd/workers/reconciliation-worker/main.go

Build Docker images

docker build -f Dockerfile.server -t cdc-api-server .
docker build -f Dockerfile.sync-worker -t cdc-sync-worker .
docker build -f Dockerfile.reconciliation-worker -t cdc-reconciliation-worker .

View OpenSearch mapping

go run cmd/tools/mapping-json/main.go | jq .

Terraform to provision infrastructure

cd terraform
terraform init
terraform plan -out=tfplan
terraform apply tfplan

Name		Name	Last commit message	Last commit date
Latest commit History 14 Commits
cmd		cmd
e2e		e2e
internal		internal
opensearch		opensearch
pkg/constants		pkg/constants
postgres		postgres
scripts		scripts
terraform		terraform
tests/integration		tests/integration
.gitignore		.gitignore
ARCHITECTURE.md		ARCHITECTURE.md
Dockerfile.reconciliation-worker		Dockerfile.reconciliation-worker
Dockerfile.server		Dockerfile.server
Dockerfile.sync-worker		Dockerfile.sync-worker
README.md		README.md
debezium-connector.json		debezium-connector.json
docker-compose.yml		docker-compose.yml
go.mod		go.mod
go.sum		go.sum

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Postgres CDC to OpenSearch Sync

🏗️ Architecture

✨ Features

Real-time Synchronization

Search Capabilities

Reconciliation

📦 Project Structure

🚀 Quick Start

Prerequisites

Setup

🔌 API Endpoints

Search Projects

Get Projects by User

Get Projects by Hashtag(s)

Health Check

⚙️ Configuration

🧪 Testing

Quick Start

Test Coverage

Manual Testing

1. Insert a new project

2. Search for it (should appear within 2 seconds)

3. Update the project

4. Add users to the project

5. Search by user

6. Delete the project

🏗️ Design Decisions

Batching Strategy

Deduplication

Immediate Deletes

Reconciliation Worker

Repository Pattern

📊 Performance Characteristics

📝 Development

Run locally

Build Docker images

View OpenSearch mapping

Terraform to provision infrastructure

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