{"id":515953,"date":"2023-01-03T09:09:00","date_gmt":"2023-01-03T08:09:00","guid":{"rendered":"https:\/\/www.devoteam.com\/expert-view\/where-to-build-your-data-lake-google-cloud\/"},"modified":"2025-06-12T14:07:10","modified_gmt":"2025-06-12T12:07:10","slug":"where-to-build-your-data-lake-google-cloud","status":"publish","type":"expert-view","link":"https:\/\/devoteam.info\/en-se\/expert-view\/where-to-build-your-data-lake-google-cloud\/","title":{"rendered":"Where to build your datalake on Google Cloud"},"content":{"rendered":"\n

Comparing the strengths and weaknesses of Google Cloud solutions like Cloud Storage, BigQuery, and Cloud SQL to build a data lake that suits your company’s needs.<\/p>\n\n\n\n

What is a data lake?<\/h2>\n\n\n\n

Comparing the strengths and weaknesses of Google Cloud solutions like Cloud Storage, BigQuery, and Cloud SQL to build a data lake that suits your company’s needs.Before answering the question of what the best data lake platform on Google Cloud is. It is important to first talk about the definition of a data lake and where it differs from a data warehouse. <\/p>\n\n\n\n

There are a few data lake definitions out there but for this article, we will go with the definition<\/a> of Google which states: <\/p>\n\n\n\n

\u201ca data lake is a centralised repository designed to store, process, and secure large amounts of structured, semistructured, and unstructured data. It can store data in its native format and process any variety of it, ignoring size limits<\/em>.\u201d<\/p>\n\n\n\n

Differences between a data lake and a data warehouse <\/h2>\n\n\n\n

Keeping this definition in mind we can see the differences between a data lake and your typical data warehouse. <\/p>\n\n\n\n

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  1. A data lake hosts all kinds of data and not only structured data like a data warehouse. <\/li>\n\n\n\n
  2. A data lake stores data in the exact format that it got from the source and not in a prepared enterprise data warehouse schema. <\/li>\n\n\n\n
  3. The last difference is that it will likely host a lot more data than the data warehouse so scaling in terms of storage capacity is even more important.<\/li>\n<\/ol>\n\n\n\n

    So, where should I make my data lake?<\/h2>\n\n\n\n

    Now that we have a common definition of a data lake we can tackle the question of what platform is best. As with a lot of things in life, the answer to this question depends on the environment where you pose the question. If you have a lot of unstructured data like pictures and videos then your requirements will be different than when you want to unify a lot of events and transactional databases.<\/p>\n\n\n\n

    To make this article as valuable as possible for everyone we will compare 3 Google Cloud Services (Cloud Storage<\/a>, BigQuery<\/a>, Cloud SQL<\/a>) and show you what the strong and weak points are of each service with respect to the requirements of a good data lake platform so you can see which platform works best for you company.<\/p>\n\n\n\n

    If you already know the basics of these services please continue to the next section. For the ones that need a refresher: <\/p>\n\n\n\n