TCP #41: Zero-ETL Patterns on AWS with Aurora, Redshift and OpenSearch

Part 1: How AWS Aurora Zero-ETL with Redshift and OpenSearch Can Remove Batch ETL Dependencies

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This is part 1 of the 3-part series on Zero-ETL Patterns on AWS series.

In today’s newsletter issue, I’ll explore how AWS Aurora Zero-ETL integrates with Redshift and OpenSearch to enable real-time analytics, search, and machine learning without batch ETL pipelines.

The Shift from Batch to Zero-ETL

Traditional Extract, Transform, Load (ETL) processes have long been the backbone of data integration.

However, they come with significant drawbacks:

• High Latency – Batch ETL jobs introduce delays.

• Operational Overhead – Maintaining ETL pipelines adds complexity.

• Cost Inefficiencies – Compute resources are often underutilized.

AWS introduced Zero-ETL architectures to address these challenges, eliminating the need for batch ETL by enabling real-time data replication between databases and analytics engines.

What is Zero-ETL?

Zero-ETL architectures streamline data movement by removing the need for scheduled ETL jobs.

Instead, they leverage event-driven data replication to instantly sync transactional data into data lakes, warehouses, and search engines.

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How AWS Aurora Zero-ETL Works?

Amazon Aurora now supports Zero-ETL integration with Amazon Redshift and OpenSearch, allowing you to replicate transactional data in real time.

Aurora Zero-ETL to Amazon Redshift

AWS Aurora (MySQL and PostgreSQL) can now automatically stream data to Amazon Redshift, which is available for real-time analytics.

Key Features:

• No need for scheduled ETL jobs – Data moves continuously.

• Minimal latency – Near real-time ingestion into Redshift.

• Auto-schema propagation – No manual table mapping is required.

Aurora Zero-ETL to OpenSearch

Similarly, Aurora can directly stream changes to Amazon OpenSearch Service, enabling real-time search and observability.

Key Features:

• Low-latency indexing – Data is searchable within seconds.

• High-performance full-text search – Supports real-time log and transaction searches.

• No ETL pipeline maintenance – Reduces operational burden.

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Zero-ETL Architecture: Aurora → Redshift & OpenSearch

How It Works

• Transactional Data Inserted – New data is written to Aurora.

• Change Data Capture (CDC) – Aurora captures and streams changes to Redshift and OpenSearch.

• Real-Time Analytics & Search

  • Redshift enables BI dashboards & ML analytics.

  • OpenSearch provides fast query-based search & logs processing.

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Benefits of Zero-ETL Over Traditional ETL

Traditional ETL

• Latency - Hours to days (batch)

• Complexity - Requires manual ETL Jobs

• Scalability - Limited by batch job sizes

• Cost - High (compute + storage)

• Use Cases - BI, Batch Analytics

Zero-ETL

• Latency - Near real-time (seconds)

• Complexity - Fully managed & automated

• Scalability - Scales elastically

• Cost - Optimized pay-as-you-go pricing

• Use Cases - Streaming, log processing, AI/ML

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Use Cases for Zero-ETL in AWS

• Real-Time Analytics Dashboards – No need for scheduled ETL pipelines; BI dashboards reflect data instantly.

• Fraud Detection & Monitoring – Capture real-time anomalies instead of waiting for batch processing.

• Log Search & Observability – Index logs instantly in OpenSearch for real-time log analytics.

• E-Commerce Product Search – Ensure inventory updates are reflected immediately in search results.

• Financial Transaction Processing – Monitor bank transactions for fraud detection as they happen.

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Setting Up AWS Aurora Zero-ETL

Step 1: Enable Zero-ETL Integration

1. Enable Zero-ETL to Redshift:

aws rds modify-db-cluster \ --db-cluster-identifier aurora-cluster \ --enable-zero-etl-integration

2. Enable Zero-ETL to OpenSearch:

aws rds modify-db-cluster \ --db-cluster-identifier aurora-cluster \ --enable-zero-etl-to-opensearch

Step 2: Verify Data Flow

• Run a transaction in Aurora:

INSERT INTO orders (id, customer_name, total_amount) VALUES (1001, 'Alice', 250.00);

• Query Redshift:

SELECT * FROM orders WHERE id = 1001;

• Search in OpenSearch:

GET _search { "query": { "match": { "customer_name": "Alice" } } }

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Best Practices for Zero-ETL on AWS

• Use Change Data Capture (CDC) wisely – Only replicate necessary data, reducing cost & latency.

• Monitor replication lag – Use Amazon CloudWatch metrics to ensure low-latency streaming.

• Partition Redshift data – Optimize query performance by partitioning time-sensitive data.

• Tune OpenSearch indexing – Avoid excessive writes that may cause shard imbalance.

• Secure data streams – Encrypt Zero-ETL pipelines using AWS KMS and IAM policies.

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Final Thoughts

Zero-ETL is an innovative approach for real-time analytics and search.

By removing batch ETL dependencies, AWS Aurora seamlessly integrates with Redshift and OpenSearch, eliminating operational overhead and delivering real-time insights at scale.

Stay tuned for next week, where I discuss Zero ETL integration between DynamoDB and Redshift.

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That’s it for today!

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Until next week — Amrut

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