Google Cloud BigQuery Reviews

Pros

It is very help full to store large unstructured data and further etl the data and used for analytics.

Cons

For Beginners it is costly. Overall very fast and reliable.

Pros

I like the serverless nature of BigQuery. It takes away most of the maintenance costs involved in maintaining and fine-tuning a data warehouse.

Cons

I didn't really like the on-demand pricing of BigQuery. Monthly costs tend to blow up excessively. I think they have a different pricing option now to resolve this though.

Alternatives Considered

Reasons for Switching to Google Cloud BigQuery

Pros

Our salesforce campaigns relies heavily on data warehouse, which is the backbone of everything we do. This data set contains both row data sets and BigQuery is used to aggregate this sets by running schedule queries on it.

Cons

This platform requires strong SQL skills. Huge dependency on tech team to fix queries sometime.

Pros

Free 1TB compute
User friendly web UI
Amazing web SQL editor

Cons

I can't find anything wrong with biguery

Alternatives Considered

Reasons for Switching to Google Cloud BigQuery

Pros

Literally everything. GBQ takes tasks like partitioning, building feeds from/to other systems simple, fine-grain access controls, plugs into Looker like a dream, built in connectors for other Google products (Search console, GA)

Cons

The permission-ing for GBQ can sometimes be vague depending on what the user is needing/wanting to do. Some roles require items that you think would be included in higher access level roles (I'm looking at you BigQuery Job User role).

Pros

importing information from Google Sheets seems like a super advantage to me, as does the ability to execute large queries without affecting performance.

Cons

I have no complaints about the tool so far

Pros

Super fast! Can handle tons of data in seconds. No worries about it slowing down. Works well with other Google stuff

Cons

Pricing is a bit confusing. Not easy to know how much it will cost. Interface could be better

Pros

I use this tool in my first professionnal experience as Data Engineer and I still use it today. I used BigQuery for Datawarehouse : make data available for everyone (data analyst, developer...).
Today, I use it too for the logs of an ELT pipeline, it's still very simple to use this tool.

Cons

It's necessary to understand how costing works in detail, especially if you have a lot of data.

Pros

It's cheap and very quick to process and query data directly.

Cons

It's bare-bones database, so doesn't come with analytical features or any visualisation or easy to use interface when compared to other solutions.

Alternatives Considered

Pros

BigQuery is powerful, easy to set up and use, and wonderfully transparent about costs. I also prefer its mechanisms for dataset partitioning over, e.g., Snowflake's.

Cons

The BigQuery UI is not great. Saved queries are messy, and scheduled queries are very difficult to maintain (to the point that they probably should not be used at all).

Alternatives Considered

Reasons for Switching to Google Cloud BigQuery

Pros

Ease of browsing through the data and seeing table structure

Cons

Not able to visualise data in BQ so had to export data or integrate visualisation tools

Alternatives Considered

Reasons for Switching to Google Cloud BigQuery

Pros

It is pretty straightforward to set up and allows for lots of data inputs. It's data visualization and statistics are amazing and provide useful insight.

Cons

It is a little more limited then it's competitors at some tasks.

Pros

Can store large amount of data, cost effective and fast

Cons

At times takes time to process queries with large amount to data

Pros

BigQuery is great at working with lots of data at a good price, especially when used with other Google Cloud tools

Cons

It can get messy when you're working with many different data sets at once, and changing existing data columns is hard.

Pros

I like the software because it is easy to use and have a good documentation to get started

Cons

It is expensive to use for smaller businesses

Pros

We use Big Query for store the information of every client's CRM, its cheap and scalable

Cons

You will need a programmer to get the integration done properly, but is not too hard

Pros

Google Cloud BigQuery is a powerful and user-friendly software for data warehousing and analytics. It can easily handle extremely large datasets, making it perfect for businesses that process and analyze massive amounts of data. The queries are executed quickly, even on large datasets, allowing for efficient data analysis and insights. The user interface is intuitive and easy to navigate, making it accessible for users of all skill levels. It integrates seamlessly with other Google Cloud products, such as Google Analytics and Google Cloud Storage, which allows for a streamlined workflow. The pricing is pay-per-use and the cost is generally lower for larger amounts of data, which makes it cost-effective. Additionally, it offers high performance, flexibility, and strong security features.

Cons

Google Cloud BigQuery is a great tool for data warehousing and analytics. One thing to keep in mind is that it can have a steep learning curve for those who are not familiar with SQL and data warehousing concepts. Additionally, it may not be as customizable as some other data warehousing and analytics tools. But overall, it offers a wide range of functionalities and a user-friendly interface, making it a great option for many use cases. I've found it to be a reliable and efficient tool for processing and analyzing large datasets.

Pros

For someone like me who works on the complete cycle of the data, it turns out to be a very good tool, since it allows us to do the complete cycle, from the initial step that is to put together a good ETL, clean our data, and be able to present it in a dashboard

Cons

once the table is created it is difficult to edit the columns, so you have to delete it

when you use the data stream, your data is in a cache, and you can't manipulate it until a couple of hours have passed

Alternatives Considered

Reasons for Switching to Google Cloud BigQuery

Pros

Google Cloud BigQuery is cloud-based data warehouse allows super fast querying data. It simplifies data integration process that is cost effective as well.

Cons

Queries also result in lot of redundant data. It cannot be used to substitute a relational database. In some cases it does not accept special characters. Managing an enterprise data, in case of other than flat tables may not be easy.

Pros

If you work with Google Stack in your company, using BigQuery makes sense. It's cloud, it's fast and it's easy to keep and update.

Cons

It's not so easy as some other tools. But in the other hand, it's part of Google Stack and you have easy information to get in the net.

Pros

Seamless integration with our data in G-sheets, Airtable, and other sources. Data visualizations / BI dashboards (using DS) at rock-bottom cost.

Cons

The number and type of data visualizations could be improved. Help system is not extensive (but with Stack Overflow, you'll be fine). The "stickiness" (persistence) and flexibility/customizability of filters needs work.

Pros

The sandbox supports up to 4 ( I think) projects that you can work on for free. This is great for people who are just starting out and BigQuery is very affordable as a whole. The pre-installed datasets are convenient and also cover various topics.

Cons

The interface could be optimized. Currently loading up multiple datasets on the same project and / or opening multiple tabs for queries makes everything really confusing and hard to navigate .

Pros

There is a plethora of already available datasets on BigQuery. Most of them won't be related to topics that interest you but are still very useful. The UI is simple,there aren't any unnecessary features that can confuse you when it comes to using BigQuery. The program is 100% scale-able and can cover data in any size.

Cons

For some people it might be an issue that BigQuery is better suited to work alongside R and not Python.If you do not opt for a flat rate and end up having a large quantity of data to deal with, BigQuery can get pricey.

Pros

Allow to import data in seconds from third party data sources, even there is an option to create multiple dashboards to visualize & analyses the data for marketing, sales purposes and so on depends on use cases.

Cons

Cost is very high with big data queries and also UI can be more improved specifically navigation and dragging options

Pros

It's probably the best SQL tool I have ever used. Ultra-scalable. Big query does not care if your a making a query of 100 MB or of 1T. It super efficient.

Cons

The only one thing I would improve is the debugging. Sometimes when you make complex SQL queries, the debugging tool does not help a lot finding the problem.