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  4. Starburst Unveils Fully Managed 'Icehouse' for Near Real-Time Analytics on the Open Data Lakehouse

Starburst Unveils Fully Managed 'Icehouse' for Near Real-Time Analytics on the Open Data Lakehouse

Icehouse on Galaxy simplifies data analytics, reduces costs, and enables AI/ML workloads with an open data lakehouse architecture.

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Tom Smith
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Apr. 24, 24 · News
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Starburst, the open data lakehouse company, has announced the launch of its fully managed Icehouse implementation on Starburst Galaxy, a move that promises to simplify data analytics workflows, improve performance, and reduce costs for developers, engineers, and architects. The Icehouse architecture, which combines the power of open-source Trino and Apache Iceberg, aims to provide a scalable, cost-effective, and high-performance solution for near real-time analytics without the risk of vendor lock-in.

Justin Borgman, co-founder and CEO of Starburst, emphasized the significance of this release, stating, "Adding a fully managed Icehouse implementation to Starburst Galaxy marks a significant milestone in our journey to provide the most advanced and user-friendly open data analytics platform available."

The Importance of an Open Data Lakehouse Architecture

As organizations increasingly turn to data lakehouses to power interactive applications and run their businesses, the need for an open architecture has become more apparent. Cloud data warehouses like Snowflake, while popular, can become prohibitively expensive as data volumes grow, leaving companies feeling locked in and unable to control their data destiny.

Borgman explained, "This breaks that model apart, turns it on its head, and says you can store data in iceberg, you can query it with Starburst, and you get the same performance, the same functionality at a fraction of the price. And you own your data."

The Icehouse architecture, as outlined in the Icehouse Manifesto, combines the Trino query engine with the Apache Iceberg table format to deliver powerful scalability, cost-effectiveness, and query performance. This open approach is already being used by tech giants like Netflix, Apple, Shopify, and Stripe, demonstrating its viability for handling large-scale data analytics.

Starburst's Fully Managed Icehouse Solution

Starburst's Icehouse implementation on Galaxy takes the open data lakehouse concept a step further by providing a fully managed, end-to-end platform that addresses the challenges of data ingestion, governance, management, and optimization at scale. With Starburst's Icehouse, customers can benefit from:

  1. Near real-time data ingestion at petabyte scale into managed Iceberg tables
  2. SQL-based data preparation and optimization for production use
  3. Automatic query performance improvement through Starburst Warp Speed's auto-tuning capabilities
  4. Integration with existing data tools, frameworks, and ecosystems
  5. Deployment flexibility across on-premises, cloud, and hybrid environments

For developers and data teams, this means a more streamlined workflow, reduced time-to-insights, and the ability to focus on building data-driven applications rather than managing infrastructure.

The Cost and Performance Benefits

One of the key advantages of Starburst's Icehouse is its potential for significant cost savings compared to traditional data warehousing approaches. In both internal and third-party benchmarking, Starburst has demonstrated a 50% or greater reduction in costs, with some customers reporting up to 10x savings on compute.

Borgman noted, "In both our own benchmarking and independent third-party benchmarking, we are generally half the price, sometimes less than half the cost. So pretty significant savings on just dollars and cents."

This cost efficiency is achieved through a consumption-based pricing model, where customers only pay for the compute resources they use. Additionally, by decoupling storage from compute and leveraging low-cost cloud object storage like Amazon S3, Azure Data Lake, and Google Cloud Storage, companies can avoid the high costs associated with vendor-managed solutions.

Enabling AI and Machine Learning Workloads

As artificial intelligence (AI) and large language models (LLMs) become increasingly important for businesses, the need for efficient data management and analytics solutions has never been greater. Starburst's Icehouse is well-positioned to support these workloads by providing the necessary data governance, privacy, and security features.

Jay Chen, Vice President of Product Marketing at Starburst, highlighted the platform's capabilities, saying, "The governance and privacy aspect is one of the things that we do really well on the platform side of this. Working with Iceberg and Trino provides the ability to filter out, mask, and read or control access to PII information."

With Starburst, companies can maintain control over their valuable data assets while leveraging the power of AI and LLMs. By filtering and masking sensitive information, creating custom data products, and managing access control, organizations can build their own proprietary models without the risk of data leakage.

The Future of Starburst's Icehouse

Starburst's commitment to an open data lakehouse architecture extends beyond this initial release. The company plans to continue investing in and expanding its Icehouse offering, with a focus on making data ingestion even easier and providing more options for customers to free up their data.

Chen emphasized the company's dedication to this initiative, stating, "This announcement is the beginning of what we're doing. There's going to be a lot of a lot more product developments that we'll be announcing in the coming quarters."

Developers, engineers, and architects can expect to see further enhancements and integrations in the coming quarters, building on the solid foundation of Trino and Apache Iceberg. As more organizations adopt this open approach to data analytics, Starburst is well-positioned to lead the way in delivering powerful, flexible, and cost-effective solutions.

Conclusion

The launch of Starburst's fully managed Icehouse on Galaxy marks a significant milestone in the evolution of open data lakehouses. By combining the power of Trino and Apache Iceberg with a user-friendly, end-to-end platform, Starburst is empowering developers, engineers, and architects to build the next generation of data-driven applications with greater efficiency, performance, and cost-effectiveness.

As Borgman concluded, "Open source and open platforms are the way to build architectures that stand the test of time."

As companies continue to grapple with the challenges of managing and analyzing ever-growing volumes of data, the importance of an open, flexible, and scalable architecture cannot be overstated. With Starburst's Icehouse, organizations now have a compelling alternative to proprietary data warehousing solutions – one that puts control back in the hands of the customer and opens the door to new possibilities in AI, machine learning, and beyond.

For developers, engineers, and architects looking to simplify their data analytics workflows, reduce costs, and future-proof their data infrastructure, Starburst's Icehouse on Galaxy is a solution worth exploring.

Data management Data (computing) Data lake Data warehouse

Opinions expressed by DZone contributors are their own.

Related

  • Exploring Slowly Changing Dimensions in Data Warehousing
  • Unlocking Data Insights and Architecture: Data Warehouses, Lakes, and Lakehouses
  • Data Warehouses: The Undying Titans of Information Storage
  • Dagster: A New Data Orchestrator To Bring Data Closer to Business Value

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