ClickHouse is an open-source columnar database management system (DBMS) for online analytical processing (OLAP).
This instructor-led, live training (online or onsite) is aimed at developers and IT professionals who wish to set up, manage, and use ClickHouse for processing SQL queries faster than traditional database management systems.
By the end of this training, participants will be able to:
- Install and configure ClickHouse.
- Understand the features and architecture of ClickHouse.
- Know the differences between ClickHouse and other database systems (MySQL, PostgreSQL, etc.).
- Configure user authentication, roles, and access controls in ClickHouse.
- Perform SQL queries, manipulate data, and manage tables in ClickHouse.
- Apply administrative tools and techniques to optimize performance.
- Implement custom integrations with external systems (MySQL, PostgreSQL, MongoDB, Apache Kafka, etc.).
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
- An understanding of relational databases
- Experience with SQL
- IT professionals
- ClickHouse vs MySQL vs Oracle
- Overview of ClickHouse features and architecture
Understanding Column-Oriented Databases
- Setting up the environment
- Installing ClickHouse
- Connecting to the database
Managing Users and Roles
- Role-Based Access Control (RBAC)
- XML vs SQL configuration
- Users, roles, and privileges
Working with the ClickHouse Database
- SQL syntax, functions, and operators
- Creating and modifying tables
- Loading data
- Creating a schema
- Running analytic queries
- Using views, indexes, and arrays
Administering the ClickHouse Database
- Replication and sharding
- Resource utilization
- Backing up and restoring data
- Optimizing performance
Integrating ClickHouse with External Systems
- ODBC and JDBC
- HDFS, Amazon S3, and EmbeddedRocksDB
- MySQL, PostgreSQL, SQLite, and Hive
- MongoDB and RabbitMQ
- Apache Kafka
Summary and Next Steps