# Apache Iceberg tables

Published articles for Apache Iceberg tables.

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## Optimizing Apache Iceberg tables for real-time analytics

DevFeed: [Optimizing Apache Iceberg tables for real-time analytics](<https://devfeed.tech/articles/optimizing-apache-iceberg-tables-for-real-time-analytics-18585.md>)

Original publisher: [Read original article](<https://www.tinybird.co/blog/optimizing-apache-iceberg-tables-for-real-time-analytics>)

Author: Alberto Romeu

Published: 2025-06-03T10:00:00Z

Content type: tutorial

Language: en

Sources: [Tinybird](<https://devfeed.tech/sources/tinybird.md>)

Topics: [Apache Iceberg](<https://devfeed.tech/topics/apache-iceberg.md>), [Apache Iceberg tables](<https://devfeed.tech/topics/apache-iceberg-tables.md>), [real-time](<https://devfeed.tech/topics/real-time.md>), [Sorting](<https://devfeed.tech/topics/sorting.md>), [systems](<https://devfeed.tech/topics/systems.md>)

Tags: [apache-iceberg](<https://devfeed.tech/tags/apache-iceberg.md>), [apache-iceberg-tables](<https://devfeed.tech/tags/apache-iceberg-tables.md>), [high-performance](<https://devfeed.tech/tags/high-performance.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [partitioning](<https://devfeed.tech/tags/partitioning.md>), [performance](<https://devfeed.tech/tags/performance.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [scalable-analytics-architecture](<https://devfeed.tech/tags/scalable-analytics-architecture.md>), [sorting](<https://devfeed.tech/tags/sorting.md>), [systems](<https://devfeed.tech/tags/systems.md>)

### AI overview

A tutorial on using Apache Iceberg partitioning, sorting, and compaction features to build high-performance real-time analytics systems.

### Source excerpt

Learn how to use Iceberg's partitioning, sorting, and compaction features to build high-performance real-time analytics systems

## What are Apache Iceberg tables? Benefits and challenges | Redpanda

DevFeed: [What are Apache Iceberg tables? Benefits and challenges | Redpanda](<https://devfeed.tech/articles/what-are-apache-iceberg-tables-benefits-and-challenges-redpanda-12675.md>)

Original publisher: [Read original article](<https://www.redpanda.com/blog/apache-iceberg-tables-benefits-challenges>)

Author: Redpanda

Published: 2025-05-21T00:00:00Z

Content type: article

Language: en

Sources: [Redpanda](<https://devfeed.tech/sources/redpanda.md>)

Topics: [Apache Iceberg](<https://devfeed.tech/topics/apache-iceberg.md>), [datasets](<https://devfeed.tech/topics/datasets.md>), [data-processing](<https://devfeed.tech/topics/data-processing.md>), [Scalability](<https://devfeed.tech/topics/scalability.md>), [Architecture & Design](<https://devfeed.tech/topics/architecture-design.md>), [Streaming](<https://devfeed.tech/topics/streaming.md>), [Netflix](<https://devfeed.tech/topics/netflix.md>)

Tags: [amazon-redshift](<https://devfeed.tech/tags/amazon-redshift.md>), [analytics](<https://devfeed.tech/tags/analytics.md>), [apache-flink](<https://devfeed.tech/tags/apache-flink.md>), [apache-iceberg](<https://devfeed.tech/tags/apache-iceberg.md>), [apache-iceberg-acid-compliance](<https://devfeed.tech/tags/apache-iceberg-acid-compliance.md>), [apache-iceberg-architecture](<https://devfeed.tech/tags/apache-iceberg-architecture.md>), [apache-iceberg-challenges](<https://devfeed.tech/tags/apache-iceberg-challenges.md>), [apache-iceberg-metadata-management](<https://devfeed.tech/tags/apache-iceberg-metadata-management.md>), [apache-iceberg-table-format](<https://devfeed.tech/tags/apache-iceberg-table-format.md>), [apache-iceberg-tables](<https://devfeed.tech/tags/apache-iceberg-tables.md>), [apache-iceberg-vs-data-lakes](<https://devfeed.tech/tags/apache-iceberg-vs-data-lakes.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [benefits-of-apache-iceberg](<https://devfeed.tech/tags/benefits-of-apache-iceberg.md>), [data](<https://devfeed.tech/tags/data.md>), [data-lakes-and-apache-iceberg](<https://devfeed.tech/tags/data-lakes-and-apache-iceberg.md>), [datasets](<https://devfeed.tech/tags/datasets.md>), [fundamentals](<https://devfeed.tech/tags/fundamentals.md>), [managing-large-datasets-with-apache-iceberg](<https://devfeed.tech/tags/managing-large-datasets-with-apache-iceberg.md>), [netflix](<https://devfeed.tech/tags/netflix.md>), [object-storage](<https://devfeed.tech/tags/object-storage.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [pipelines](<https://devfeed.tech/tags/pipelines.md>), [real-time-analytics-with-apache-iceberg](<https://devfeed.tech/tags/real-time-analytics-with-apache-iceberg.md>), [scalability](<https://devfeed.tech/tags/scalability.md>), [scalability-of-apache-iceberg-tables](<https://devfeed.tech/tags/scalability-of-apache-iceberg-tables.md>), [streaming](<https://devfeed.tech/tags/streaming.md>)

### AI overview

This article explains how Apache Iceberg tables add database-like structure to data lakes for large analytic datasets. It covers schemas, partitioning, metadata catalogs, version history, schema changes, data rewrites, queryability, consistency, scalability, and interoperability across batch and streaming pipelines and analytics engines.

### Source excerpt

Apache Iceberg tables introduce a reliable framework for querying large datasets in data lakes. Explore their use cases, benefits, and more.

## ClickHouse Release 25.3

DevFeed: [ClickHouse Release 25.3](<https://devfeed.tech/articles/clickhouse-release-25-3-5120.md>)

Original publisher: [Read original article](<https://clickhouse.com/blog/clickhouse-release-25-03>)

Author: ClickHouse

Published: 2025-03-27T00:00:00Z

Content type: release

Language: en

Sources: [ClickHouse Blog](<https://devfeed.tech/sources/clickhouse-blog.md>)

Topics: [clickhouse](<https://devfeed.tech/topics/clickhouse.md>), [AWS Glue](<https://devfeed.tech/topics/aws-glue.md>), [JSON](<https://devfeed.tech/topics/json.md>), [Apache Iceberg](<https://devfeed.tech/topics/apache-iceberg.md>), [Caching](<https://devfeed.tech/topics/caching.md>), [data](<https://devfeed.tech/topics/data.md>), [elasticsearch](<https://devfeed.tech/topics/elasticsearch.md>), [MongoDB](<https://devfeed.tech/topics/mongodb.md>)

Tags: [apache-iceberg](<https://devfeed.tech/tags/apache-iceberg.md>), [apache-iceberg-tables](<https://devfeed.tech/tags/apache-iceberg-tables.md>), [aws](<https://devfeed.tech/tags/aws.md>), [aws-glue](<https://devfeed.tech/tags/aws-glue.md>), [cache](<https://devfeed.tech/tags/cache.md>), [clickhouse](<https://devfeed.tech/tags/clickhouse.md>), [compression](<https://devfeed.tech/tags/compression.md>), [database](<https://devfeed.tech/tags/database.md>), [elasticsearch](<https://devfeed.tech/tags/elasticsearch.md>), [json](<https://devfeed.tech/tags/json.md>), [mongodb](<https://devfeed.tech/tags/mongodb.md>), [release](<https://devfeed.tech/tags/release.md>)

### AI overview

ClickHouse 25.3 introduces 18 features, 13 performance optimizations, and 48 bug fixes. The release adds AWS Glue and Unity catalog support, a query condition cache, automatic S3 query parallelization, new array functions, and a production-ready JSON data type.

### Source excerpt

ClickHouse 25.3 is out! In this post, we highlight expanded Lakehouse catalog support with AWS Glue and Unity, the new query condition cache, automatic parallelization for external data sources, two new handy functions--and the GA of our new JSON type.