Google Cloud BigQuery Reviews & Product Details

Google Cloud BigQuery is an incredibly serverless data warehousing solution.

I appreciate its ability to handle large datasets efficiently without the need for infrastructure management.

The SQL-like querying is intuitive, and the speed at which queries return results is impressive, even for complex analytics tasks.

The platform integrates seamlessly with other Google Cloud services and third-party tools, making it easy to build data pipelines and workflows. Review collected by and hosted on G2.com.

While BigQuery is a robust platform, it can be expensive if usage is not carefully monitored. The pricing model, based on data scanned, may lead to unexpectedly high costs for complex queries or frequent data analysis. Additionally, while the documentation is thorough, getting started can be overwhelming for users who are new to cloud data warehouses. Customer support is helpful but sometimes slower during peak times.

Major downside is things that are expected to work, don't seem to be supported, especially like the internal working of how "LIMIT" works. Review collected by and hosted on G2.com.

We use Google Cloud Big Query to host our applications backend because it offers performance and compatibility in addition to seamless deployment and management. Data fetching is fast and costs less compared to other major competitors. It can be implemented easily and easy to use with all other Google's solutions for App hosting as well as Work collaboration. We use it to host our applications that being used by thousands of customers everyday. Review collected by and hosted on G2.com.

Features could be better but it compensates for that with better compatibility and tracking and logging capabilities. Review collected by and hosted on G2.com.

Honestly, what I love most about BigQuery is how easy it makes working with huge amounts of data. It's part my of may daily work. You know, like, really huge. It's like having this super-powerful engine that you don't have to worry about maintaining. You just throw your data in, and it just... works.

I think the biggest thing is that I don't have to deal with servers. No more worrying about setting things up, scaling, or any of that. It's just there, ready to go. Review collected by and hosted on G2.com.

The biggest thing that can get you is the cost. If you're not careful, those queries, especially the complex ones on huge datasets, can really add up. You've got to be smart about optimising them, or you'll get a surprise bill. Review collected by and hosted on G2.com.

BigQuery makes handling massive datasets fast, simple, and cost-efficient with minimal infrastructure overhead. Review collected by and hosted on G2.com.

Its ability to process terabytes of data in seconds using standard SQL is impressive. The serverless architecture eliminates the need to manage infrastructure, and seamless integration with tools like Data Studio, Looker, and Cloud Functions makes analytics pipelines much easier to build and automate. Review collected by and hosted on G2.com.

The most helpful thing about BigQuery is how fast and scalable it is—you can run complex SQL queries on massive datasets in seconds without worrying about infrastructure. I love that it’s fully serverless, so there’s no setup or maintenance, and the integration with other Google Cloud tools makes it easy to build data pipelines or dashboards. Pricing based on data scanned keeps costs predictable, and the performance has been consistently solid for our team. Review collected by and hosted on G2.com.

One downside is that costs can add up quickly if you’re not careful with how much data your queries scan. It also lacks some built-in data transformation or orchestration features, so you often need other tools like Dataflow or Cloud Composer. The UI can feel a bit clunky for complex workflows, and debugging SQL in the web interface isn’t always the most convenient. Review collected by and hosted on G2.com.

BigQuery is fast, fully serverless, easy to integrate with other Google Cloud tools, and handles large datasets effortlessly using simple SQL. Review collected by and hosted on G2.com.

BigQuery can get expensive for frequent or complex queries, has some limitations in job monitoring and debugging, and its SQL features and UI still feel limited compared to traditional data warehouses. Review collected by and hosted on G2.com.

Best thing which I like about Google Cloud bigquery is that it just not query store data within it, but we can also query external source like stored data in GCS. Review collected by and hosted on G2.com.

Nothing much to dislike about bigquery as it resolved our problems. Review collected by and hosted on G2.com.

Its so easy and simple to use if you're familiar with SQL, and the fact that the query scales based on the memory & compute usage makes it cheap if you can write an efficient query Review collected by and hosted on G2.com.

the hidden cost if you're writing inefficient query can ramp up the cost pretty heavily Review collected by and hosted on G2.com.

The console is descriptive and I've found performance to match my expectations. The Python API is also pretty slick for querying data that I need. Review collected by and hosted on G2.com.

There are some odd query-type quirks that don't always make sense coming from SQL. I've been notified some of my queries are quite expensive in ways I didn't expect. Review collected by and hosted on G2.com.

I like that BigQuery is serverless, fast, and scales effortlessly for petabyte-scale analytics. It supports standard SQL, integrates well with Google tools, and even lets you run ML models directly on your data without moving it. Review collected by and hosted on G2.com.

BigQuery can get expensive with frequent or complex queries, especially if not optimized. It also has query performance limitations for very high-concurrency, low-latency use cases compared to traditional OLAP databases. Review collected by and hosted on G2.com.