Have a look at some of the most notable demos we built this year, and how they help people feel the speed of ClickHouse through real, hands-on examples.
Overview
The article reviews significant demo developments at ClickHouse in 2025, highlighting various applications that showcase its performance and capabilities. It emphasizes the importance of demos in demonstrating real-world applications and experiences with ClickHouse, alongside insights from team members and notable projects.
What You'll Learn
1
How to build real-time dashboards using ClickHouse
2
Why materialized views enhance query performance in ClickHouse
3
How to leverage natural language processing with ClickHouse for data querying
4
When to use ClickHouse for observability in microservices
Prerequisites & Requirements
- Understanding of real-time data processing concepts
- Familiarity with ClickHouse and SQL
Key Questions Answered
What is StockHouse and how does it utilize ClickHouse?
StockHouse is a real-time market analytics application that streams stock and crypto data via WebSocket APIs into ClickHouse. It features a dashboard that updates within milliseconds, demonstrating ClickHouse's speed and efficiency in handling live data.
How does ClickGems provide analytics for the RubyGems ecosystem?
ClickGems offers a dedicated interface for exploring RubyGems download statistics using SQL. It aggregates raw data through materialized views, allowing users to run SQL queries directly and visualize the data effectively.
What is the purpose of AgentHouse in relation to ClickHouse?
AgentHouse showcases how ClickHouse can serve as a backend for agentic applications, enabling users to query real datasets using natural language. It generates SQL queries based on user input and provides instant answers from live data.
What does the ClickStack demo illustrate about observability?
The ClickStack demo allows users to experience observability on ClickHouse by simulating an SRE's role in investigating application incidents. It integrates logs, traces, and metrics from a microservices-based application into ClickHouse for analysis.
Key Statistics & Figures
Rows ingested by Tesla into ClickHouse
over a quadrillion rows
This showcases ClickHouse's capability to handle massive datasets efficiently.
Download history covered by ClickGems
more than 200,000 gems
This illustrates the extensive data available for analysis within the RubyGems ecosystem.
Row count for ClickPy
two trillion rows
This emphasizes the scalability of ClickHouse in handling large public datasets.
Technologies & Tools
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Database
Clickhouse
Used for real-time data analytics and querying in various demo applications.
Communication Protocol
Websocket
Facilitates real-time data streaming for applications like StockHouse.
Observability
Opentelemetry
Instrumented services in the ClickStack demo to collect logs, traces, and metrics.
Key Actionable Insights
1Leverage ClickHouse's materialized views to optimize query performance in real-time applications.By storing raw data and using materialized views for common queries, developers can ensure that their applications remain responsive and efficient, especially in data-intensive environments.
2Utilize natural language processing capabilities in ClickHouse to enhance user interaction with data.Implementing natural language interfaces can simplify data querying for non-technical users, making analytics more accessible and intuitive.
3Explore the open-source demos provided by ClickHouse to understand best practices in data ingestion and visualization.These demos serve as practical references for developers looking to implement similar solutions in their projects, ensuring they follow proven patterns.
Common Pitfalls
1
Failing to utilize materialized views can lead to slow query performance.
Without pre-aggregating data, queries may take longer to execute, especially in real-time applications where speed is critical.
Related Concepts
Real-time Data Processing
Natural Language Processing In Data Querying
Observability In Microservices Architecture