Data Lake Query Acceleration using Standalone Antalya Swarms
Antalya standalone swarms allow any ClickHouse® server to accelerate data lake queries and lower costs. Learn how to set up standalone swarms and use them.

Antalya standalone swarms allow any ClickHouse® server to accelerate data lake queries and lower costs. Learn how to set up standalone swarms and use them.

ClickHouse SQL is a powerful tool to show data lake table structure and read data from them. We’ll show it works with Iceberg tables.

Explore the Project Antalya 2026 roadmap for ClickHouse and Apache Iceberg, covering compute swarms, tiered storage, and data lake security.

Efficiently move data from ClickHouse to Iceberg using Altinity Ice with parallelization, zero-copy file registration, and automatic Parquet loading.

The new Hybrid Table Engine feature in the Project Antalya version of ClickHouse lets you query data from MergeTree and Iceberg together.

The new Antalya release is an important step in the Project Antalya roadmap that delivers better integration with data lakes and improved performance of queries over Iceberg data.

Connect ClickHouse to AWS’s new S3 Table Buckets using Iceberg, run real-time SQL on Parquet data, and build data pipelines in Altinity.Cloud.

Real-time data lakes just got real. Altinity.Cloud for ClickHouse® now supports managed Iceberg & compute swarms for fast, scalable analytics.

Recent developments in ClickHouse® and Project Antalya elevate Iceberg support to a new level – matching and in some cases outperforming MergeTree, while enabling cheap object storage and scalable, shared data systems.

Altinity Ice is an open source tool that makes it easy to set up Iceberg REST catalogs and load data with just two commands. Build Iceberg data lakes anywhere—perfect for ClickHouse® and Project Antalya users.

Discover Project Antalya: Experience ClickHouse® analytics on Iceberg storage, cutting costs by 90% and delivering up to 100x faster queries.

Large data lakes are challenging centralized analytic services. To deliver real-time analytics, databases need to work less like restaurants and more like food trucks.
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