Here's what the built-in SQL GUI looks like in BigQuery:Īnd this is what it looks like in Snowflake: The GUIs are also pretty minimal, both in terms of UI, as well as feature set. Moreover, the built-in GUIs are made only for the cloud platform you're using and their corresponding data warehousing service, which means that while they integrate with other services from the same cloud platform pretty well, they cannot incorporate or connect to different data warehouses and data sources. For example, many companies choose to use Amazon QuickSight to empower their teams to query and analyze data within Amazon Redshift.
Surprisingly, though the warehouses themselves are optimized for speed and performance, the GUIs are not necessarily purpose-built for consuming or processing large amounts of data on top of the data warehouse. Although it's great to have these GUIs tightly coupled with their data warehouse platforms, they don't always offer robust features and the cloud platform GUIs are meant for basic query and data discovery. Let's quickly look at built-in SQL GUIs first before we focus on analyzing the external ones: Data warehouses with built-in SQL GUIsĪll the major cloud data warehouses, such as Snowflake, Firebolt, Azure Synapse Analytics, Amazon Redshift, and Google BigQuery offer native SQL GUIs to let you access the data from the cloud platform's console. There are two categories of data warehouse GUIs : those that come packaged with the data warehouse (built in) and the rest that are more generic and can be connected to different data sources. This article will take you through some of the most popular SQL GUIs for data warehouses, cover their features in depth, as well as go over the pros and cons of each. While most offer a GUI (graphical user interface) to access, view, and edit data, there are also other options available which may be more powerful or useful and if you need to support the needs of other roles outside of engineering, such as data analysts, data scientists, or other business users. These days, most companies depend on one or several data warehouses, such as Snowflake, Google BigQuery, or Amazon Redshift, to store and analyze their data. This post was written with help from Kovid Rathee.
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