Why is ClickHouse better than Hadoop for Real-time Analytics?

Shiv Iyer ClickHouse, ClickHouse DBA Support, ClickHouse Hadoop, ClickHouse Internals, ClickHouse Performance

Introduction

ClickHouse is a column-oriented, open-source analytics database that is designed for real-time OLAP (online analytical processing) and OLTP (online transaction processing) use cases. It is optimized for large-scale data processing, high-performance queries, and real-time analytics.

Comparing ClickHouse with Hadoop for Real-time Analytics

Here are a few reasons why ClickHouse is recommended for real-time analytics over Hadoop:

  1. Performance: ClickHouse is designed for high-performance analytical queries and can handle millions of rows per second. It uses a column-oriented storage model, which allows it to read and process only the columns that are needed for a specific query, resulting in faster query times. Hadoop, on the other hand, is designed for batch processing, which can result in longer query times.
  2. Scalability: ClickHouse can scale horizontally by adding more machines to a cluster, allowing it to handle very large datasets. Hadoop can also scale horizontally, but it requires more resources and management.
  3. Real-time analytics: ClickHouse is optimized for real-time analytics and can process data as it is ingested, providing near real-time analytics. Hadoop, on the other hand, is designed for batch processing, so it is not well-suited for real-time analytics.
  4. Ease of use: ClickHouse has a SQL-like query language, which makes it easy to use for developers and analysts who are familiar with SQL. Hadoop, on the other hand, has a steeper learning curve, as it requires a knowledge of programming languages such as Java or Python to work with the data.
  5. Flexibility: ClickHouse supports different types of data and can be integrated with other data sources, such as Kafka, to support real-time streaming data. Hadoop is mostly used for batch processing and is less flexible.
  6. Cost: ClickHouse is open-source and is less expensive than Hadoop, which requires expensive commercial licenses.

Conclusion

It’s worth noting that each technology has its own strengths and weaknesses and the best choice depends on the specific use case. Hadoop is a powerful tool for batch processing and data warehousing, while ClickHouse is better suited for real-time analytics.

To learn more about ClickHouse v/s Hadoop, do consider reading the following articles:

 

About Shiv Iyer 216 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.
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