BigQuery and self-hosted on-prem data warehousing solutions have their own set of advantages and disadvantages, so it is important to consider your specific use case and requirements when choosing between the two options. Here are some pitfalls to keep in mind when comparing BigQuery to a self-hosted on-prem data warehousing solution, with a focus on performance, cost, and complexity.

Performance:

BigQuery's performance is typically fast and scalable, as it is designed to process massive datasets quickly and efficiently. However, performance may be affected by factors such as data size, query complexity, and concurrent usage. For complex queries or large datasets, it may take longer for BigQuery to process and return results.
Self-hosted on-prem data warehousing solutions can offer better performance in certain scenarios, especially when working with smaller datasets or executing complex queries that require more computing power. However, performance may be limited by the hardware and infrastructure available on-premises.
Cost:

BigQuery pricing is based on usage and varies depending on the amount of data processed, storage used, and queries executed. For small to medium-sized datasets, BigQuery can be cost-effective, as users only pay for the resources they use. However, for larger datasets or frequent queries, costs can quickly add up, making BigQuery more expensive than a self-hosted on-prem data warehousing solution.
Self-hosted on-prem data warehousing solutions require significant upfront costs for hardware, infrastructure, and software licenses. However, once the initial setup is complete, ongoing costs can be minimal. With a self-hosted solution, you have more control over your data and can avoid potential costs associated with data egress or accessing data from external sources.
Complexity:

Setting up and managing a BigQuery environment is relatively straightforward, as Google Cloud takes care of infrastructure and maintenance tasks. However, users need to have a certain level of technical expertise to manage the platform and optimize queries for performance and cost.
Self-hosted on-prem data warehousing solutions require significant technical expertise to set up and maintain. Users must manage hardware, software, and infrastructure, as well as perform routine maintenance and upgrades to ensure optimal performance. Additionally, self-hosted solutions may require more specialized knowledge to optimize queries and troubleshoot issues.
In summary, if cost is the most important consideration, a self-hosted on-prem data warehousing solution may be a more cost-effective option in the long run, especially for larger datasets or frequent queries. However, if performance and scalability are a top priority, and you do not want to manage infrastructure and maintenance tasks, then BigQuery may be the better choice. It's important to evaluate your specific use case and requirements to determine which option is best for you.
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