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Requires some setup and configuration
Can be challenging to use for beginnerS

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Fast and efficient processing for streaming data
Scalable and fault-tolerant

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Not as good as Hadoop for storing data
Can be difficult to debug and optimize performance issues

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Fast processing and efficient use of resources
Supports multiple programming languages

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Requires a significant amount of setup and configuration
Steep learning curve for beginners

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Scalable and fault-tolerant for storing and processing large amounts of data
Open-source and free to use

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1. SYAMSUL AFHAM BIN ROZMAN (4202033481)
2. GHINNAYATUL FITRRIYA BINTI OTHAMAN (4203003261D)

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Very reliant and fast in processing streaming data, scalable, and fault-tolerant. Kafka is widely used for real-time data pipelines, and it integrates well with other data warehouse tools like Spark, Flink, and Hadoop.

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It is a proven tool for storing and processing large amounts of data, scalable, fault-tolerant, and has a mature ecosystem. Hadoop supports various data processing engines like Hive, Pig, and Spark, making it a versatile tool for data warehousing.

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Very fast and efficient processing large-scale data, supports multiple programming languages, and has a large and active community. It is suitable for both batch and real-time processing, making it a versatile tool for data warehousing.