The announcement of AWS S3 Tables and SageMaker Lakehouse at re:Invent 2024 has caused a buzz across the data engineering community. Positioned as a managed Apache Iceberg service, AWS’s latest offering promises faster queries, lower costs, and tighter integration with its ecosystem. With these claims, AWS is taking aim at Databricks Delta Lake and other lakehouse pioneers. But is this truly a disruptive innovation, or just another chapter in the evolving lakehouse wars?
Let’s dive deep to separate the signal from the noise and explore what this means for the industry—and more importantly, for businesses already invested in Databricks Delta Lake.
🧩 Breaking Down S3 Tables
AWS’s S3 Tables, built on Apache Iceberg, promise powerful features like:
- ACID transactions
- Time travel queries
- Schema evolution
Features like automatic table maintenance (compaction, snapshot management, and stale file cleanup) simplify operations. Add tight integration with AWS services like Glue, Athena, and QuickSight, and it’s clear AWS is targeting lakehouse supremacy.
🌟 Delta Lake Still Shines Bright
Despite AWS’s innovation, Delta Lake remains a powerhouse with capabilities that Iceberg and S3 Tables can’t yet rival:
- Streaming Excellence
Delta Lake is deeply integrated with Apache Spark Structured Streaming, offering native batch and streaming support. This is crucial for businesses managing real-time analytics alongside batch pipelines. - Data Mutations Made Easy
Delta’s production-ready APIs for MERGE, UPDATE, and DELETE streamline data corrections and historical updates. Iceberg lags behind here, with limited mutation features. - Robust Schema Management
Delta Lake’s schema evolution ensures seamless adoption of changes while enforcing quality standards—critical for evolving business needs. - Governance with Unity Catalog
Databricks’ Unity Catalog surpasses Iceberg’s catalog by providing a comprehensive, collaborative governance framework. - Mature Ecosystem
Delta Lake has years of optimizations for query performance, tooling, and cross-cloud compatibility, making it ideal for scaling complex lakehouse architectures.
🔍 The AWS Catch
While S3 Tables offer exciting features, AWS’s pricing model can quickly escalate for high-frequency workloads. Costs include:
- Storage: $0.0265 per GB/month—higher than standard S3 storage.
- Compaction: $0.05 per GB processed.
- Requests: $0.004 per 1,000 GETs and $0.005 per 1,000 PUTs.
For organizations with moderate usage, AWS estimates $35 per TB/month, but real-time workloads could see significant cost increases.
Moreover S3 Tables adhere to Iceberg standards, their deep integration with AWS services means potential vendor lock-in. AWS-specific optimizations could make migrating to other platforms challenging down the line, especially for organizations seeking a multi-cloud strategy. Whereas Delta Tables UniForm allows reading from multiple formats, including Apache Iceberg.
🚀 What Does This Mean for Databricks Users?
For businesses already using Databricks Delta Lake, there’s no need to panic. AWS’s entry into the lakehouse space validates the model but doesn’t overshadow Delta’s strengths. Delta Lake remains a superior choice for enterprises needing:
- Real-time and batch processing capabilities.
- Robust data mutation support.
- A mature ecosystem with governance and collaboration tools.
At Techwards, we see this as an exciting time for the data industry. AWS’s announcement signals the growing importance of lakehouse architectures, but Delta Lake continues to lead as the most reliable and scalable foundation for modern data engineering.
🔮 Conclusion: A Bold Move, But Delta Stands Strong
AWS S3 Tables with Iceberg integration is a bold step in the lakehouse wars, promising innovation and efficiency for AWS-centric organizations. However, for businesses invested in Databricks and Delta Lake, there’s no compelling reason to switch. Delta Lake’s maturity, feature set, and enterprise focus make it the long-term, strategic choice.
What do you think? Is AWS rewriting the lakehouse rules, or does Databricks continue to dominate? Let us know your thoughts!
Stay tuned as we continue to explore the evolving world of data engineering. At Techwards, we’re committed to helping organizations navigate these changes and build scalable, secure lakehouse solutions.
Adeel Amin
Thursday Dec 06 2024
