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The Ultimate Resource Hub for Optimizing Iceberg Tables

November 22, 2024
/
Karthic Rao
Fredson Lewis
Engineering

At e6data, we are big admirers of Apache Iceberg. We're witnessing a steep increase in its adoption, with our customers running E6data's query engine for heavy workloads.

While we were scrambling for resources on the internet to optimize Iceberg, why not curate it for the rest of the community?

Here's a curated collection of links, guides, and insights to help you discover the best practices for optimizing your Iceberg tables.  

- Optimization Strategies for Iceberg Tables by Cloudera    
- Compaction in Apache Iceberg: Fine-Tuning Your Iceberg Table’s Data Files by Dremio    
- Improving performance with Iceberg sorted tables by Starburst    
- Partitioning and Indexing in Apache Iceberg by IOMETE    
- Optimizing read performance by AWS    
- Maintaining tables by using compaction by AWS    
- Iceberg 101: A Guide to Iceberg Partitioning by Upsolver    
- Iceberg Tables Optimization by Upsolver    
- How Z-Ordering in Apache Iceberg Helps Improve Performance by Dremio    
- Z-ORDER sorting during compaction by IOMETE    
- Iceberg 101: Ten Tips to Optimize Performance by Upsolver    
- Optimizing Iceberg tables by AWS    
- https://iceberg.apache.org/docs/1.6.0/performance/ Apache Iceberg official documentation    
- Manage and Optimize Iceberg tables for efficient data storage and querying by AWS    
- Best practices for optimizing Apache Iceberg workloads by AWS

Check out our GitHub repository for more resources on optimizing lakehouse tables.

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FAQs

How does e6data reduce Snowflake compute costs without slowing queries?
e6data is powered by the industry’s only atomic architecture. Rather than scaling in step jumps (L x 1 -> L x 2), e6data scales atomically, by as little as 1 vCPU. In production with widely varying loads, this translates to > 60% TCO savings.
Do I have to move out of Snowflake?
No, we fit right into your existing data architecture across cloud, on-prem, catalog, governance, table formats, BI tools, and more.

Does e6data speed up Iceberg on Snowflake?
Yes, depending on your workload, you can see anywhere up to 10x faster speeds through our native and advanced Iceberg support. 

Snowflake supports Iceberg. But how do you get data there in real time?
Our real-time streaming ingest streams Kafka or SDK data straight into Iceberg—no Flink. Landing within 60 seconds and auto-registering each snapshot for instant querying.

How long does it take to deploy e6data alongside Snowflake?
Sign up the form and get your instance started. You can deploy it to any cloud, region, deployment model, without copying or migrating any data from Snowflake.

FAQs

Does the hub link to official Apache Iceberg performance documentation?
Yes. It includes a direct link to the Apache Iceberg “performance” documentation page.
Are AWS-specific best-practice guides included?
Yes. The list features several AWS documents on general best practices, optimizing reads and writes, storage tuning, compaction, and running Iceberg workloads on Amazon S3.
Is there a recommended guide focused on Iceberg partitioning?
Yes. The hub links to “Iceberg 101: A Guide to Iceberg Partitioning,” which concentrates entirely on effective partition design.
Where can I find additional lakehouse optimization materials beyond the article?
A GitHub repository curated by e6data is linked at the end of the post for further exploration.

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