Google Cloud BigQuery Reviews

“Affordable scalable cloud data platform”

Pros

From my experience, it handles large amounts of data really well while still staying affordable, especially when I connect it with other Google Cloud tools. I like that it doesn't become expensive even when the data size grows.

Cons

Things can get messy when working with multiple datasets and modifying existing columns is also quite difficult.

“High performance large dataset system”

Pros

It can store huge volumes of data and still stay fast which makes it very useful for my day-to-day work. I don't run into slowdowns even when dealing with heavy datasets.

Cons

At times, query processing can take longer than expected when working with large volumes of data which slows things down a bit during heavier workloads.

“Fast large scale analytics warehouse”

Pros

Working with this tool has been really helpful for data warehousing and analytics in my case. It manages extremely large datasets without any trouble which is important for the kind of data I handle. Queries also run quickly even on big datasets, so I can easily pull insights without waiting too long. I find the interface simple to work with and I can move around it without confusion. It also connects well with other Google Cloud tools like Google Analytics and Google Cloud Storage which keeps everything in one workflow for me. The pay-as-you-go pricing is something I personally like because it stays cost-effective as usage increases. On top of that, I still get strong performance, flexibility and great security features.

Cons

It's a strong tool for data warehousing and analytics overall but I've noticed it comes with a learning curve, especially if you're not already comfortable with SQL or data warehousing concepts. It also doesn't feel as customizable as some other tools out there but despite that, it still delivers reliable performance and handles large datasets efficiently.

“Connected google cloud analytics platform”

Pros

From my side, connecting data from Google Sheets, Airtable and other sources has been very smooth. I can also build dashboards for reporting and visual analysis without spending a lot which helps me keep costs under control.

Cons

The available data visualizations could definitely be improved and the help documentation isn't very extensive, though I usually manage with external resources like Stack Overflow. Filtering can also feel a bit limited in terms of persistence and flexibility which affects usability at times.

“Quick multi dashboard reporting tool”

Pros

I'm able to pull data from third-party sources in just a few seconds and I often create multiple dashboards depending on whether I'm working on marketing or sales analysis.

Cons

Costs can get very high when dealing with large-scale queries and the interface could be improved, especially around navigation and moving between elements more smoothly.

“Multi source dashboard analytics tool”

Pros

I can import data from external sources very quickly and I usually build multiple dashboards so I can analyze different areas like marketing and sales based on my needs.

Cons

The UI in general could use refinement, especially in navigation and drag-and-drop handling when dealing with large data environments.

“ETL dashboard data pipeline tool”

Pros

In my case, I work with the full data cycle and this tool helps me a lot with it. I can build ETL processes, clean the data and then present everything in dashboards without needing separate tools for each step.

Cons

Once a table is created, editing columns becomes difficult, often requiring deletion and recreation. With data streaming, there's also a delay because the data sits in cache for a while before it can be fully manipulated.

“SQL heavy technical analytics tool”

Pros

In my work with Salesforce campaigns, the data warehouse plays a key role since it acts as the base for everything. I deal with both raw datasets and grouped data and I run scheduled queries to organize and analyze them properly.

Cons

Strong SQL skills are pretty much required and there's often a heavy dependency on technical support or engineering teams to resolve complex queries.

“Learning friendly sandbox dataset tool”

Pros

The sandbox option has been helpful for me since it lets me work on a few projects for free. I also like that it comes with ready datasets on different topics which makes practice and learning easier.

Cons

The interface could be better optimized. Working with multiple datasets in one project or juggling several query tabs at once can quickly become confusing.

“Beginner friendly cloud warehouse tool”

Pros

Getting started was very easy for me. As a beginner, I liked having public datasets for practice and I also found it helpful that it connects with other Google Cloud tools, so I don't need extra software to expand my work.

Cons

I haven't really found anything I dislike so far, so there's nothing negative to report from my side.

“Fast large scale SQL tool”

Pros

From my experience, this is one of the best SQL tools I've used. Even when I run extremely large queries, it stays fast and efficient without slowing down.

Cons

Debugging complex SQL queries isn't always very helpful, since the tool doesn't consistently pinpoint issues clearly.

“BI integrated data platform”

Pros

I like how easily it connects with BI tools and different data sources. One thing I personally find useful is how simple it is to connect Google Sheets as a data source for reporting.

Cons

Pricing isn't always easy and takes some time to fully understand, even though it is generally fair and affordable.

“Fast data warehouse visualization tool”

Pros

I use it as my main data warehouse and the query speed has been extremely fast in my case. I also connect it with Google Data Studio to analyze and visualize data more effectively.

Cons

It can become quite expensive if you're running queries frequently which is something to keep in mind.