How ClickHouse Uses AWS

The article discusses how PeerDB facilitates large-scale PostgreSQL migrations, specifically achieving a 1TB migration in just 2 hours.

This article explains how ClickHouse optimizes Top-N queries (ORDER BY . LIMIT N) using granule-level data skipping indexes.

ClickHouse 25.

ClickHouse 25. 9 introduces streaming secondary indices, a fundamental change to how secondary indexes (minmax, set, bloom filter, vector, text) are evaluated during query execution.

The article discusses the new functionality in ClickHouse that allows for multiple lightweight projections to behave like true secondary indexes, significantly enhancing query performance without d...

The article discusses the development of chDB, a Python library that integrates ClickHouse with Pandas DataFrames for high-performance SQL querying.

ClickHouse version 25. 11 introduces significant enhancements, including 24 new features, 27 performance optimizations, and 97 bug fixes.

This article benchmarks five major cloud data warehouses—Snowflake, Databricks, ClickHouse Cloud, BigQuery, and Redshift—across various scales of data to compare their cost-performance.

This article provides a detailed analysis of how the five major cloud data warehouses—Snowflake, Databricks, ClickHouse Cloud, Google BigQuery, and Amazon Redshift Serverless—calculate compute cost...

This article discusses the transition from OpenTelemetry (OTel) to Rotel, an open-source Rust project that enhances tracing capabilities at petabyte scale.

The article details the journey of upgrading the chDB kernel from ClickHouse v25. 5 to v25. 8. 2.

This article details the transformation of ClickHouse's internal data warehouse from a traditional BI-first approach to an AI-first model, significantly enhancing user accessibility to analytics.

ClickPipes for PostgreSQL has introduced support for failover replication slots, enhancing reliability and flexibility for users.

ClickHouse version 25. 10 introduces significant enhancements, including 20 new features, 30 performance optimizations, and 103 bug fixes.

The article discusses the potential of lakehouses using open table formats like Apache Iceberg and Delta Lake for observability, highlighting their advantages in scalability, cost-effectiveness, an...

The article discusses the new capabilities of ClickHouse Cloud to query Iceberg and Delta Lake tables through the DataLakeCatalog engine.

ClickHouse Release 25. 9 introduces significant enhancements, including 25 new features, 22 performance optimizations, and 83 bug fixes.

ClickHouse version 25. 8 introduces 45 new features, 47 performance optimizations, and 119 bug fixes, enhancing its capabilities as a high-performance analytical database.

The article discusses how ClickHouse Cloud has achieved the capability to scale complex GROUP BY queries across thousands of cores, processing over 100 billion rows in under a second.

This article discusses the process of creating reproducible ZIP archives for AWS Lambda functions, focusing on challenges such as file order, timestamp management, and OS compatibility.

This article discusses the implementation of Change Data Capture (CDC) from Delta Lake to ClickHouse, detailing the architecture, components, and a reference implementation in Python.

This article compares the UPDATE performance of ClickHouse and PostgreSQL, highlighting ClickHouse's significant speed advantages in bulk updates while also acknowledging PostgreSQL's strengths in ...

ClickHouse Release 25.

This article discusses the significant performance improvements achieved in ClickHouse's SQL UPDATE operations, demonstrating how they can be up to 1,000× faster than traditional mutation methods t...

The article discusses the transition of ClickHouse Cloud to a fully stateless compute architecture, enabled by the introduction of a Shared Catalog.

This article benchmarks join-heavy SQL queries across ClickHouse, Databricks, and Snowflake, demonstrating that ClickHouse outperforms both competitors in speed and cost across various data scales.

ClickHouse version 25.

This article discusses the development of a distributed cache for ClickHouse Cloud, aimed at providing low-latency access to hot data across compute nodes.

The article discusses how ClickHouse efficiently queries Parquet files, a key storage format for Lakehouse architectures, without requiring data ingestion.

ClickHouse version 25. 4 introduces 25 new features, 23 performance optimizations, and 58 bug fixes, enhancing query performance and community contributions.

The article discusses the introduction of lazy materialization in ClickHouse, a powerful analytical database, which optimizes query performance by delaying the reading of column data until it is ac...

The article discusses how Dash0 transitioned to using ClickHouse as a core database technology for their observability platform, leveraging its efficiency and scalability to handle OpenTelemetry da...

ClickHouse version 25.

This article discusses the implementation of ClickHouse's Bring Your Own Cloud (BYOC) model on AWS, detailing the benefits of customer-controlled cloud environments and the challenges faced during ...

The article details a complex debugging journey faced by ClickHouse engineers as they investigated a mysterious CPU spike in their cloud infrastructure on GCP.

This article explores the various input formats supported by ClickHouse for data ingestion, focusing on performance and efficiency.

ClickHouse version 25. 1 introduces significant enhancements, including 15 new features, 36 performance optimizations, and 77 bug fixes.

The article discusses the One Billion Documents JSON Challenge, comparing the performance of ClickHouse against other popular databases like MongoDB, Elasticsearch, DuckDB, and PostgreSQL in storin...

This article discusses the open sourcing of kubenetmon, a tool developed by ClickHouse to monitor data transfer in ClickHouse Cloud.

ClickHouse version 24. 12 introduces 16 new features, 16 performance optimizations, and 36 bug fixes, enhancing usability and performance for users.

ClickHouse version 24. 11 introduces significant enhancements including 9 new features, 15 performance optimizations, and 68 bug fixes.

ClickHouse version 24.

ClickHouse version 24. 7 introduces significant enhancements, including 18 new features, 12 performance optimizations, and 76 bug fixes.

This article compares ClickHouse and Elasticsearch in terms of performance for large-scale data analytics, particularly focusing on `count(*)` aggregations over billions of rows.

The article introduces adsb. exposed, an interactive tool for visualizing and analyzing ADS-B flight data using ClickHouse.

ClickHouse version 24. 3 introduces 12 new features, 18 performance optimizations, and 60 bug fixes, enhancing query analysis and optimization capabilities.

This article explores how ClickHouse can be utilized as a feature store to train machine learning models, specifically focusing on the integration with Featureform.

This article details the development of a ClickHouse-powered logging platform, named LogHouse, which efficiently manages over 19 PiB of log data while significantly reducing costs compared to tradi...

This article discusses ClickHouse's performance in handling large datasets, specifically addressing the 1 trillion row challenge.

This article explores the use of Apache Iceberg and ClickHouse to analyze global internet speeds using the Ookla dataset.