Google Cloud BigQuery Reviews & Product Details - Page 2

There are Lots of features in Bigquery which are helpful to developers working in it.Even Non technicals can run there queries in big query using the help of Gemini.You can also estimate the cost behind each query before even running it.It is very easy in use also for new comers.i do work with Bigquery almost all time of day. Review collected by and hosted on G2.com.

There are some things which are not available like bigquery cannot be directly integrated with solutons like Microsoft Sharepoint. Review collected by and hosted on G2.com.

No need to manage infrastructure; Google handles scaling, maintenance, and performance tuning automatically. Works well with other Google Cloud services (Cloud Storage, Dataflow, AI/ML tools) and external platforms like Looker, Tableau, and BigQuery ML for advanced analytics.Can process streaming data in real-time, making it ideal for use cases like fraud detection and live analytics. I don’t have to manage infrastructure, scaling, or indexing manually. It allows you to run SQL queries on massive datasets without worrying about performance tuning. Review collected by and hosted on G2.com.

BigQuery follows a pay-per-query model, meaning costs can spike unexpectedly if queries are not optimized. Review collected by and hosted on G2.com.

it is begginer friendly for on boarding and comphernsiive docmentation and ad-hoc querying and sheduled batch jobs. and native interactions with google eco systems make ease of imolementation having roberst customer support.it is comfertble for frequency of use Review collected by and hosted on G2.com.

it makes billing misunderstanding and learning curve for advanced features and limitation ui depended users Review collected by and hosted on G2.com.

Very fast processing, Computing power is very good. Even crores of records also it'll process in 5-10secs. Well Organised, UI is good. Even non techie can understand the things in no time. Scheduling queries creating views is super easy. We can even run AI/ML models in bigquery studio no need to explicitly build the models. Review collected by and hosted on G2.com.

Even if you have saved views name in your dataset and if you refresh the page because of network issues or any other issues it wont show your views names instead it'll show untitled query in studio. Then again you have go to your view path and have to open and edit it from your left side panel.

If we are working on small project then it is fine But when we're working on big projects where we have to open 10-15 views and edit it then that time it'll be hectic. Review collected by and hosted on G2.com.

Google Cloud provides tight integration with other Google services, such as BigQuery, Pub/Sub, and TensorFlow, making it a favorite for data analytics and machine learning tasks. High-performing infrastructure, particularly for AI/ML workloads, Its Ease to Use and Ease to implement, its also have a good customer support and its globaly highly use cloud so we also using frequently using. Review collected by and hosted on G2.com.

For beginners or those migrating from other platforms, understanding and navigating Google Cloud's ecosystem can be overwhelming. Also comparitively high cost Review collected by and hosted on G2.com.

Bigquery is one of that serverless warehouse where you don't have to thing about about compute, since it is managed by GCP, we as a engineers only needs to worry about how to store the data in BQ with effective partitioning and clustering strategy.

Bigquery as shifted the tradition from decoupled compute and storage ( spark + warehouse ) to a tightly coupled architecture which has drastically simplified the data platform architecture. Review collected by and hosted on G2.com.

I believe costing needs to be controlled, I have seen couple of engineers firing an very expensive queries unknowingly which has significantly increase the billing.

I would recommend following changes:

1) There should be pop up kind of thing that we can implement which can warn the users ( on how many GB of data they are scanning along with its cost ).

2) Bigquery can also provide an optional features to the organisation where they can limit the data scan for their data users. ( lets say company decide to cap the data scan to 10 GB, none of the user should be able to query more than that )

3) With the help of AI, if BQ can provide recommendation based on the query patterns and the table structure, few ways in which they can optimise table scan would be really beneficial. Review collected by and hosted on G2.com.

BigQuery is very good at handling large datasets with high speed and scalability and integration with GA4 and Looker enables help in analytics and actionable insights. Review collected by and hosted on G2.com.

The cost structure becomes expensive for complex queries. Also SQL interface has a learning curve for beginners. Review collected by and hosted on G2.com.

My company, Randstad, uses BigQuery as our data warehouse to store all our lead information and marketing metrics. It pulls numbers from various sources and then creates master data sources, which we use for the performance dashboards we present to internal stakeholders. More recently, we have been using Big Query to host our historical data from Google Analytics. Review collected by and hosted on G2.com.

One of the things I dislike about BigQuery is that you need to be somewhat technical to use the product, it is confusing if you are not. A lot of people in my organization won't even go to the platform because it stresses them out. Also, if you don't know where the data is hosted it is hard to know where everything is. Review collected by and hosted on G2.com.

It is very assist full with putting away huge unstructured information and further etl the information and utilized for examination. Customer Support is great Review collected by and hosted on G2.com.

Seller secure in, deceiving specialized documentation, lacking help, over the top expensive. Review collected by and hosted on G2.com.

I am able to use BigQuery to query my large integrated Google Analytics database and visualize the results in a metter of seconds very simply. Documentation was widely available for me to make BigQuery a regular part of my workflow. Review collected by and hosted on G2.com.

There is a bit of a learning curve, but with AI solutions and the widely available documentation, it isn't too difficult to get started. Review collected by and hosted on G2.com.