StarTree, the cloud-based, real-time analytics company, is unveiling support for Apache Iceberg in StarTree Cloud—the real-time analytics platform for user-facing applications, powered by Apache Pinot. With this support, StarTree Cloud can be utilized as both the analytic and serving layer on top of Iceberg, enabling interactive insights to flow to internal and external applications directly from the data lakehouse.
While Apache Iceberg and Parquet have grown in popularity as open table formats for data management in the lakehouse, the lack of a query engine is its foremost challenge. Any query engines built around Apache Iceberg and Parquet are often ill-equipped to meet the performance demands of external-facing, high-concurrency analytical applications, forcing many enterprises to avoid serving data directly from their lakehouse, according to StarTree. As a result, due to having to rely on reverse ETL pipelines or transforming data into proprietary formats, enterprises face increased latency, complexity, and cost.
At its core, this release expands what’s possible with Apache Iceberg—”transforming it from a passive storage format into a real-time backend capable of powering customer-facing applications and AI agents with high concurrency serving thousands of simultaneous users with consistent speed and reliability,” according to StarTree. By offering real-time query acceleration directly on native Iceberg tables, StarTree enables applications to deliver live insights from the lakehouse—without any operational trade-offs.
“We’re seeing explosive growth in customer-facing, and increasingly agent-facing, data products that demand sub-second responsiveness and fresh insights. At the same time, Iceberg is emerging as the industry standard for managing historical data at scale,” said Kishore Gopalakrishna, co-founder and CEO, StarTree. “As these two trends converge, StarTree is delivering unique value by acting as a real-time serving layer for Iceberg empowering companies to serve millions of external users and AI agents securely, scalably, and without moving data.”
“Apache Iceberg is rapidly becoming the de facto standard for managing large-scale analytical data in the open data lakehouse—adoption has surged by over 60% year-over-year, according to theCUBE Research,” explained Paul Nashawaty, principal analyst at theCUBE Research. “But as more organizations look to power real-time, customer-facing applications with this data, a clear gap has emerged in the market. StarTree’s ability to serve Iceberg data with sub-second latency and without data duplication is a unique and timely advancement. It addresses a critical performance need for accessing historical data in modern data products.”
StarTree Cloud, built for low-latency, high-concurrency access, is ideal for supporting interactive dashboards, real-time data products, and operational workloads with strict SLAs, according to the company. It offers capabilities such as:
- Native support for Apache Iceberg and Parquet
- Real-time indexing and aggregations, including support for numerical, text, JSON, and geo indexes
- Intelligent materialized views via the StarTree Index
- Local caching and pruning for low-latency, high-concurrency queries
- Serve directly from Iceberg, eliminating data movement
- Intelligent prefetching from Iceberg, reducing irrelevant data scans
To learn more about StarTree, please visit https://startree.ai/.