Amazon Redshift Spectrum vs Apache Kylin: What are the differences?

# Introduction

1. **Deployment**: Amazon Redshift Spectrum is a fully managed service offered by AWS that allows you to run queries against exabytes of data in S3 without having to load or transform the data. On the other hand, Apache Kylin needs to be deployed on a Hadoop cluster, which requires more setup and maintenance compared to Redshift Spectrum.
2. **Query Processing Engine**: Redshift Spectrum uses the same query engine as Amazon Redshift, which is based on PostgreSQL, while Apache Kylin uses a distributed computing engine to parallelize queries and process data cubes efficiently.
3. **Data Source**: Amazon Redshift Spectrum is integrated with Amazon S3 for data storage and retrieval, enabling queries to be run directly on data stored in S3. In contrast, Apache Kylin primarily works with data stored in Hadoop-based distributed file systems like HDFS.
4. **Data Model**: Apache Kylin uses a pre-aggregated data model known as data cubes to accelerate query performance for OLAP (Online Analytical Processing) workloads. Redshift Spectrum, on the other hand, does not require pre-aggregated data models and can query data directly from S3.
5. **Cost**: The pricing model for Amazon Redshift Spectrum is based on the amount of data scanned from S3, making it a cost-effective solution for sporadic or unpredictable query workloads. Apache Kylin, being an open-source project, may have lower upfront costs but could require more resources for setup, maintenance, and scaling.
6. **Scalability**: Redshift Spectrum allows you to dynamically scale compute resources based on query demands, which can help handle sudden spikes in workload effectively. However, Apache Kylin's scalability may be limited by the underlying Hadoop cluster's resources and configuration.

In Summary, the key differences between Amazon Redshift Spectrum and Apache Kylin lie in their deployment model, query processing engine, data source integration, data model approach, cost structure, and scalability capabilities.