Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.
$6.25
per TiB (after the 1st 1 TiB per month, which is free)
Google Sheets
Score 8.7 out of 10
N/A
Google Sheets is the spreadsheet app available on Google Workspace, or standalone, with a free plan for personal use and accessible via mobile apps for iOS and Android.
Main reason is how it integrates directly with the google ecosystem which really facilitates the automatization proceses for the whole company. This ensures that sales and all the other departments have the correct information on a daily bases with a ease of use with day to day …
Compared to PostgreSQL and MySQL, Google BigQuery is faster and more scalable for large datasets. It’s serverless, so there’s no need to manage infrastructure. We chose Google BigQuery for its ease of use built-in analytics features
I have used other data manipulation tools like SQL Server and Google BigQuery feels more intuitive, Google provides so much documentation and tutorials that getting to know the software is not only easy but even satisfactory, so I'd say Google BigQuery is very superior to that …
Event-based data can be captured seamlessly from our data layers (and exported to Google BigQuery). When events like page-views, clicks, add-to-cart are tracked, Google BigQuery can help efficiently with running queries to observe patterns in user behaviour. That intermediate step of trying to "untangle" event data is resolved by Google BigQuery. A scenario where it could possibly be less appropriate is when analysing "granular" details (like small changes to a database happening very frequently).
Google Sheets is great for just recording tabular information that needs to be shared with and/or edited by multiple people. Sharing and collaborating is especially convenient because Sheets is designed to be browser-based; while Excel has a browser version, it's limited compared to the desktop app. Google Sheets's editing, suggesting, commenting, and viewing permissions settings are absolutely perfect for my department. Google Sheets does not handle large datasets well. It does not load in a timely manner and often freezes. Apps Scripts fail to process large amounts of data.
GSheet data can be linked to a BigQuery table and the data in that sheet is ingested in realtime into BigQuery. It's a live 'sync' which means it supports insertions, deletions, and alterations. The only limitation here is the schema'; this remains static once the table is created.
Seamless integration with other GCP products.
A simple pipeline might look like this:-
GForms -> GSheets -> BigQuery -> Looker
It all links up really well and with ease.
One instance holds many projects.
Separating data into datamarts or datameshes is really easy in BigQuery, since one BigQuery instance can hold multiple projects; which are isolated collections of datasets.
Please expand the availability of documentation, tutorials, and community forums to provide developers with comprehensive support and guidance on using Google BigQuery effectively for their projects.
If possible, simplify the pricing model and provide clearer cost breakdowns to help users understand and plan for expenses when using Google BigQuery. Also, some cost reduction is welcome.
It still misses the process of importing data into Google BigQuery. Probably, by improving compatibility with different data formats and sources and reducing the complexity of data ingestion workflows, it can be made to work.
We have to use this product as its a 3rd party supplier choice to utilise this product for their data side backend so will not be likely we will move away from this product in the future unless the 3rd party supplier decides to change data vendors.
I think overall it is easy to use. I haven't done anything from the development side but an more of an end user of reporting tables built in Google BigQuery. I connect data visualization tools like Tableau or Power BI to the BigQuery reporting tables to analyze trends and create complex dashboards.
Overall the formula functions could improve but there's workarounds for them. Utilzing different formulas or approaches for building out accounting schedules. While collebrating with multiple team members and different departments being able to go in and see where others are on the sheets is helpful. Google Sheets overall is a great product
I have never had any significant issues with Google Big Query. It always seems to be up and running properly when I need it. I cannot recall any times where I received any kind of application errors or unplanned outages. If there were any they were resolved quickly by my IT team so I didn't notice them.
Like most Google products, Google Sheets rarely has outages or slowness, and when it does, connection is always momentarily restored. I can't recall a time when I've been unable to access Google Sheets but able to access other sites just fine. That said, errors aren't uncommon when handling large data volume. You know what they say about using spreadsheets as databases, but sometimes it's just the most convenient option, especially for smaller or one-off projects, and not being able to store large amounts of data hampers our ability to move quickly with scrappy prototypes or full solutions. It would be great if we could better integrate our data manipulation (Apps Script) with big data in the sheet.
I think Google Big Query's performance is in the acceptable range. Sometimes larger datasets are somewhat sluggish to load but for most of our applications it performs at a reasonable speed. We do have some reports that include a lot of complex calculations and others that run on granular store level data that so sometimes take a bit longer to load which can be frustrating.
Again, Google Sheets is no exception to Google's general high speed and reliability, but load times can be slow for larger amounts of data. I've used Sheets with Zapier and have used the Python API, and speed has never been an issue.
BigQuery can be difficult to support because it is so solid as a product. Many of the issues you will see are related to your own data sets, however you may see issues importing data and managing jobs. If this occurs, it can be a challenge to get to speak to the correct person who can help you.
I have never contacted Google Sheets support, but Google Sheets makes it very easy to report an issue or suggest a feature from Sheets itself (Help > Help Sheets improve), and I've had mostly good experiences with support for other Google products.
PowerBI can connect to GA4 for example but the data processing is more complicated and it takes longer to create dashboards. Azure is great once the data import has been configured but it's not an easy task for small businesses as it is with BigQuery.
The major reason I use Google Sheets over Microsoft Excel and Apple Numbers is for its ability to allow multiple users to access and work on the same spreadsheet at once. This is incredibly more efficient and effective than updating and sending copies upon copies of the same Excel or Numbers spreadsheet back and forth as email attachments.
I'm not involved with the purchase, but I assume everything goes smoothly and that the pricing structure is predictable and reasonable. We do not get surprise fees.
We have continued to expand out use of Google Big Query over the years. I'd say its flexibility and scalability is actually quite good. It also integrates well with other tools like Tableau and Power BI. It has served the needs of multiple data sources across multiple departments within my company.
Google Sheets works very well with multiple users. It's convenient to see in real-time who is collaborating in a sheet, down to the specific cell that they're viewing/editing. Linking Sheets across departments is convenient with the IMPORTRANGE function.
Google Support has kindly provide individual support and consultants to assist with the integration work. In the circumstance where the consultants are not present to support with the work, Google Support Helpline will always be available to answer to the queries without having to wait for more than 3 days.
Previously, running complex queries on our on-premise data warehouse could take hours. Google BigQuery processes the same queries in minutes. We estimate it saves our team at least 25% of their time.
We can target our marketing campaigns very easily and understand our customer behaviour. It lets us personalize marketing campaigns and product recommendations and experience at least a 20% improvement in overall campaign performance.
Now, we only pay for the resources we use. Saved $1 million annually on data infrastructure and data storage costs compared to our previous solution.
