Likelihood to Recommend Google BigQuery really shines in scenarios requiring real-time analytics on large data streams and predictive analytics with its machine learning integration. Teams have been using it extensively all over. However, it may not be the best fit for organizations dealing with small datasets because of the higher costs. And also, it might not be the best fit for highly complex data transformations, where simpler or more specialized solutions could be more appropriate.
Read full review Google Sheets is a great tool mostly for people in the finance department such as accountants who have to analyze hundreds of transactions. The software makes it easy to organize data and handle some analysis. Also, when it comes to data presentation, Google Sheets offers some of the best features. However, this is not to sat people outside the finance docket cannot benefit from this software. It is a great tool to have when handling data.
Read full review Pros Its serverless architecture and underlying Dremel technology are incredibly fast even on complex datasets. I can get answers to my questions almost instantly, without waiting hours for traditional data warehouses to churn through the data. Previously, our data was scattered across various databases and spreadsheets and getting a holistic view was pretty difficult. Google BigQuery acts as a central repository and consolidates everything in one place to join data sets and find hidden patterns. Running reports on our old systems used to take forever. Google BigQuery's crazy fast query speed lets us get insights from massive datasets in seconds. Read full review It is a cloud-based platform. You can work in the same file simultaneously with your colleagues. It allows you to share files much faster. It allows you to access your Google Sheet files whenever you like and wherever you like if you have stable internet connection. It has great integration with other Google software. Google Sheets is very user-friendly and very intuitive to use. Read full review Cons It is challenging to predict costs due to BigQuery's pay-per-query pricing model. User-friendly cost estimation tools, along with improved budget alerting features, could help users better manage and predict expenses. The BigQuery interface is less intuitive. A more user-friendly interface, enhanced documentation, and built-in tutorial systems could make BigQuery more accessible to a broader audience. Read full review Pivot tables are different but could be improved upon; sort, totals, filters When entering negative numbers as the first in a formula you need to remember to "+-100+25" instead of "-100+25" The power of the internet of course makes it easy to find solution, but the help function is not easily available Color coding changes on the cell, but there is not an easy way to click on a cell and use the selected color; like excel Read full review Likelihood to Renew 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.
Read full review It is easy to use, free of charge for basic functionality, and easy to share with people within or outside your team or company
Read full review Usability web UI is easy and convenient. Many RDBMS clients such as aqua data studio, Dbeaver data grid, and others connect. Range of well-documented APIs available. The range of features keeps expanding, increasing similar features to traditional RDBMS such as Oracle and DB2
Read full review Support Rating 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.
Read full review Alternatives Considered I have used
Snowflake and
DataGrip for data retrieval as well as Google BigQuery and can say that all these tools compete for head to head. It is very difficult to say which is better than the other but some features provided by Google BigQuery give it an edge over the others. For example, the reliability of Google is unmatchable by others. One thing that I really like is the ability to integrate Data Studio so easily with Google BigQuery.
Read full review 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.
Read full review Contract Terms and Pricing Model None so far. Very satisfied with the transparency on contract terms and pricing model.
Read full review Professional Services 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.
Read full review Return on Investment Pricing has been very reasonable for us. The first 10 GB of storage is free each month and costs start at 2 cents per GB per month after that. For example, if you store 1 terabyte (TB) for a month, then the cost would be $20. Streaming data inserts start at 1 cent per 200 megabytes (MBs). The first 1 TB of queries is free, with additional analysis at $5 per TB thereafter. Meta data operations are free. Big Query helps reduce the bar for data analytics, ML and AI. BQ takes care of mundane tasks and streamlines for easy data processing, consumption. The most impressive thing is the ML and AI integration as SQL functions, so the need for moving data around is minimized. The visuals of ML models is very helpful to fine tune training, model building and prediction, etc. Read full review We've used it to prepare quick budgets, presentations for funds that have helped raise money It has helped us quickly analyze raw data, collaboratively. it has helped us work more efficiently by making it easier to work from one sheet and not lose track of versions by passing around attached documents Read full review ScreenShots Google BigQuery Screenshots