BigQuery allows you to quickly analyze logs from your systems to identify the severity of issues. It integrates well with other Google Cloud services, such as Cloud Logging, where you can easily manipulate various data types and analyze all logs.
Red Team Operator at Argentina Red Team
Analyzes logs from systems to identify the severity of issues but lacks integrations
Pros and Cons
- "BigQuery excels at data analysis. It processes vast amounts of information using its advanced architecture and sophisticated querying capabilities, making it crucial for critical insights and safe for handling sensitive data."
- "BigQuery should integrate with other tools, such as Cloud Logging and Local Studio, to enhance its capabilities further and enable powerful and innovative analyses."
What is our primary use case?
What is most valuable?
BigQuery excels at data analysis. It processes vast amounts of information using its advanced architecture and sophisticated querying capabilities, making it crucial for critical insights and safe for handling sensitive data.
What needs improvement?
BigQuery should integrate with other tools, such as Cloud Logging and Local Studio, to enhance its capabilities further and enable powerful and innovative analyses.
For how long have I used the solution?
I have been using BigQuery for two years.
Buyer's Guide
BigQuery
February 2025
Learn what your peers think about BigQuery. Get advice and tips from experienced pros sharing their opinions. Updated: February 2025.
832,138 professionals have used our research since 2012.
Which solution did I use previously and why did I switch?
I have opted for Fireye, Elasticsearch, and Alcon. One principal difference is that BigQuery starts with machine learning and WAN implementations, while you can implement VMware or other active boxes. Therefore, it is recommended that cloud VMs be used for BigQuery processes. You can execute jobs in the cloud, such as VMware.
For instance, you can compute analytics for email, apply filters, and manipulate weather data. It provides higher efficiency, though exact benchmarks are unclear. Additionally, starting the query flow login request can also be advantageous.
How was the initial setup?
The initial setup is automatic. It requires one person. You need to log in to the Google Cloud platform, import the necessary package into your query, and then you can start querying your data.
If you need a solid CRM solution integrated with Azure, you'll need knowledgeable people to support it. Three individuals can form a strong CRM team connected to Azure, leveraging BigQuery.
What was our ROI?
You can use BigQuery to generate and manage large datasets efficiently. Whether using a flexible integrated environment like Dataflow or a local studio, BigQuery provides powerful tools for querying and analyzing data.
What's my experience with pricing, setup cost, and licensing?
The product is free of cost.
What other advice do I have?
Setting up BigQuery on GCP is crucial. When creating a service account, you define the permissions required for project identification or access monitoring systems.
You configure policies using IAM roles to manage access permissions effectively within GCP. These roles govern the service accounts created for specific tasks such as data processing, system monitoring, or other service integrations. When you activate these policies, a JSON token is generated. This token can authenticate and authorize access to Google services like BigQuery or other third-party applications.
Moreover, by configuring VMs to match data processing requirements, you ensure that the data is securely handled by the applications associated with the service accounts. This setup enables seamless communication between your applications and Google services, facilitating efficient data acquisition and processing.
Overall, I rate the solution a seven out of ten.
Which deployment model are you using for this solution?
Public Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Last updated: Jun 26, 2024
Flag as inappropriateData Quality Specialist at a energy/utilities company with 201-500 employees
Facilitate data exploration with centralized data and table visualization
Pros and Cons
- "Its integration with other tools like Atlan through a Google Chrome extension is highly beneficial."
- "It can be slower and more problematic compared to other platforms such as Snowflake."
What is our primary use case?
I usually need to catalog. In my case, it's more related to data governance. I need to catalog information from BigQuery. I want to ensure the data quality tool is in sync with BigQuery, so I go to BigQuery and do queries to make sure it was synced with Atlan, for example, for data quality tools. I create validation rules and need to write the rule in BigQuery to create a query there, see how long it takes to run, and evaluate its performance in a data quality tool.
How has it helped my organization?
What I have seen is that they are using BigQuery as a central repository. They bring dispersed information to BigQuery, which facilitates exploring the data and gaining insights. Consequently, it improves operations, response time, and the business overall.
What is most valuable?
As a user, I have liked using BigQuery to create queries. They have a table explorer feature that allows you to select a table, choose fields, and generate queries easily, which significantly facilitates my workflow. I also appreciate the lineage feature, which shows how tables relate to each other and enables end-to-end usage visualization.
Furthermore, its integration with other tools like Atlan through a Google Chrome extension is highly beneficial. Using BigQuery's central repository brings dispersed information together, which facilitates exploring the data and gaining insights. Consequently, it improves operations, response time, and the business overall.
What needs improvement?
There are integration challenges, particularly with performance when exporting data to BigQuery from other tools like Qualitics. It can be slower and more problematic compared to other platforms such as Snowflake.
For how long have I used the solution?
I have been working with BigQuery for one year.
What do I think about the stability of the solution?
I have not seen a lot of problems, so I would say BigQuery is quite stable.
What do I think about the scalability of the solution?
In my opinion, BigQuery is very scalable yet has some limitations regarding performance that are not always as required.
How are customer service and support?
I don't have direct contact with BigQuery's support team. Our organization manages this through internal communication, and I contact my company’s team when issues arise.
How would you rate customer service and support?
Positive
What other advice do I have?
I would recommend using BigQuery because it's a very good tool, easy to manage, and similar to other databases. Those familiar with SQL Server or Oracle can adapt to BigQuery easily. It's a scalable cloud solution.
Overall, I would rate BigQuery as nine out of ten.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Last updated: Dec 3, 2024
Flag as inappropriateBuyer's Guide
BigQuery
February 2025
Learn what your peers think about BigQuery. Get advice and tips from experienced pros sharing their opinions. Updated: February 2025.
832,138 professionals have used our research since 2012.
Consaltant
A powerful and user-friendly solution for efficient data analytics and processing with serverless architecture, seamless scalability, SQL-like queries and cost-effective pay-as-you-go model
Pros and Cons
- "One of the most significant advantages lies in the decoupling of storage and compute which allows to independently scale storage and compute resources, with the added benefit of extremely cost-effective storage akin to object storage solutions."
- "The main challenges are in the areas of performance and cost optimizations."
What is our primary use case?
It is a pivotal component in enterprise data architecture, and crucial in data lake operations, whether supporting data warehouses or functioning as part of a broader data lake ecosystem.
What is most valuable?
One of the most significant advantages lies in the decoupling of storage and compute which allows to independently scale storage and compute resources, with the added benefit of extremely cost-effective storage akin to object storage solutions. Its unique architecture not only provides robust enterprise data warehouse capabilities but also seamlessly integrates with data lake functionalities.
What needs improvement?
The main challenges are in the areas of performance and cost optimizations. Achieving optimal results demands a certain level of familiarity with the platform's internals. The key point for improvement lies in the performance optimization.
For how long have I used the solution?
I have been working with it for three months.
What do I think about the stability of the solution?
It exhibits a high level of stability and security, there are no notable issues in these aspects. I would rate it nine out of ten.
What do I think about the scalability of the solution?
It is designed to seamlessly scale with the growing demands of data processing, there are no issues with it. I would rate it nine out of ten.
How are customer service and support?
The technical support is commendable. However, there is room for improvement in the availability of resources and documentation from a technological standpoint. I would rate it seven out of ten.
How would you rate customer service and support?
Neutral
Which solution did I use previously and why did I switch?
In the landscape of enterprise data warehouses, BigQuery stands out as a superior choice when compared to alternatives like Azure Synapse, AWS Redshift, and Snowflake. While Snowflake is known for its higher costs, and Redshift is perceived as both complex and expensive, Azure Synapse presents its own set of constraints with its MPP architecture and reliance on an RDBMS in-between. BigQuery, on the other hand, has a distinct edge with its seamless migration process, vast capabilities, and a harmonious balance of storage, computing, cost-effectiveness, and performance efficiency. This is particularly evident as organizations and professionals, including myself, have experienced ease in migrating from other vendors to BigQuery. Drawing from my extensive experience working across various cloud platforms such as AWS, Azure, and Snowflake, BigQuery consistently emerges as a robust and preferable solution.
How was the initial setup?
The initial setup is straightforward.
What's my experience with pricing, setup cost, and licensing?
Its cost structure operates on a pay-as-you-go model. I would rate it seven out of ten.
What other advice do I have?
Whether for small, medium, or large enterprises, it is a recommendable choice. Its pricing model makes it accessible and manageable based on your usage. Given that many individuals and businesses already have Gmail accounts and utilize Google Cloud workspaces, incorporating BigQuery into operations is seamless. Moreover, a complimentary reporting tool, Looker Studio, is available for free, enhancing the reporting capabilities on BigQuery or via Google Sheets. Overall, I would rate it eight out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Google
Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
Expert Analyst at a healthcare company with 5,001-10,000 employees
Enables fast data analysis with SQL proficiency for a flexible environment
Pros and Cons
- "The initial setup is simple."
- "BigQuery has a very nice interface that you can easily learn if you know SQL."
- "When I open many of the Google Cloud products, I am in an environment that I do not feel familiar with; it is a little overwhelming."
- "When I open many of the Google Cloud products, I am in an environment that I do not feel familiar with; it is a little overwhelming."
What is our primary use case?
We are migrating all the data to BigQuery from SaaS. We are creating projects and using it for data analysis in the healthcare environment, specifically for Medicare and Medicaid.
What is most valuable?
The use of SQL is valuable. I am very familiar with the flexibility of the environment. It is not just a cloud environment but also offers a nice interface. BigQuery has a very nice interface that you can easily learn if you know SQL. It is really fast because it can process millions of rows in just a matter of one or two seconds. It is fast.
What needs improvement?
When I open many of the Google Cloud products, I am in an environment that I do not feel familiar with; it is a little overwhelming. In general, if I know SQL and start playing around, it will start making sense.
However, the first impression is a little overwhelming, with all the wire pins and options. It is probably not for beginners, yet for people very familiar with SQL. They will figure out what to choose or do since every option probably has a technical definition or a pre-assumed concept. If they improve something, it might be a different product with a more friendly environment, although it is friendly now. Every little thing I do assumes I know what I am doing.
For how long have I used the solution?
I have used the solution for six months.
What do I think about the scalability of the solution?
The scalability is definitely good because we are migrating to the cloud since the computers on the premises or the big database we need are no longer enough. Google Cloud offers bigger spaces, however, it requires detailed administration of the databases.
How are customer service and support?
I do not receive customer service from Google Cloud, however, we have internal customer support.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
We used Microsoft TSS before. I do not use it now.
How was the initial setup?
The initial setup is simple. It can be complicated if you are migrating from another platform.
What other advice do I have?
I would say the overall rating is nine out of ten.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Last updated: Jan 26, 2025
Flag as inappropriateAssociate Consultant (Data Engineer) at MediaAgility
Provides flexibility and is competitively priced
Pros and Cons
- "The most valuable features of BigQuery is that it supports standard SQL and provides good performance."
What is our primary use case?
We use BigQuery to perform data warehouse migration for clients willing to move to GCP from their on-premise solution.
What is most valuable?
The solution's pricing is really competitive compared to other peers. The most valuable features of BigQuery is that it supports standard SQL and provides good performance.
For how long have I used the solution?
I have been using BigQuery for three years.
What do I think about the stability of the solution?
I rate BigQuery a nine out of ten for stability.
What do I think about the scalability of the solution?
Around 30 to 40 users use BigQuery in our organization.
I rate BigQuery ten out of ten for scalability.
Which solution did I use previously and why did I switch?
I previously worked with Microsoft SQL Server.
How was the initial setup?
The solution’s initial setup is very easy. You just have to spin up a data set and start using it.
I rate BigQuery ten out of ten for the ease of its initial setup.
What about the implementation team?
The solution can be deployed by one person in a few minutes.
What's my experience with pricing, setup cost, and licensing?
The solution's pricing is cheaper compared to other solutions. On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a two or three out of ten.
What other advice do I have?
Potential users can trust BigQuery without any second thoughts. The solution's pricing is great compared to other solutions. The solution provides more flexibility and supports standard SQL, and anyone coming out from a different platform would not face any challenges adopting BigQuery.
Overall, I rate BigQuery a nine out of ten.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Sr Manager at a transportation company with 10,001+ employees
Everything they advertised worked exactly as promised
Pros and Cons
- "We basically used it to store server data and generate reports for enterprise architects. It was a valuable tool for our enterprise design architect."
- "I would like to see version-based implementation and a fallback arrangement for data stored in BigQuery storage. These are some features I'm interested in."
What is our primary use case?
We basically used it to store server data and generate reports for enterprise architects. It was a valuable tool for our enterprise design architect.
What is most valuable?
Everything they advertised or listed worked exactly as promised. That was advantageous to us.
What needs improvement?
In future releases, I would like to see more pre-defined aggregated forms. After using BigQuery, we need to use the data in an enterprise architecture dimensional data model. So, having pre-defined aggregated forms would be helpful.
Additionally, I would like to see version-based implementation and a fallback arrangement for data stored in BigQuery storage. These are some features I'm interested in.
For how long have I used the solution?
I have experience with BigQuery.
What about the implementation team?
When I joined the company, BigQuery was already implemented by our team.
What's my experience with pricing, setup cost, and licensing?
It is a cheap solution.
What other advice do I have?
I would recommend getting a clear understanding of BigQuery's functionalities and what it's best suited for. If your needs align with its capabilities, then you should definitely proceed.
BigQuery offers fantastic features, but it's important to understand its purpose beforehand. Otherwise, you might face difficulties later on.
Overall, I would rate the solution an eight out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Google
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Full-stack Developer at ViewersLogic
Fast, flexible, scalable, stable, and easy to learn
Pros and Cons
- "What I like most about BigQuery is that it's fast and flexible. Another advantage of BigQuery is that it's easy to learn."
- "An area for improvement in BigQuery is its UI because it's not working very well. Pricing for the solution is also very high."
What is our primary use case?
My company uses BigQuery as a data warehouse.
What is most valuable?
What I like most about BigQuery is that it's fast and flexible.
Another advantage of BigQuery is that it's easy to learn.
You can also use it from anywhere.
What needs improvement?
An area for improvement in BigQuery is its UI because it's not working very well.
Pricing for the solution is also very high.
In general, though, I like the solution very much.
For how long have I used the solution?
I've been using BigQuery for six months now.
What do I think about the stability of the solution?
I found BigQuery stable in my six months of using it, and I'd rate its stability as ten out of ten.
What do I think about the scalability of the solution?
BigQuery is a scalable solution, and it's a nine out of ten in terms of scalability.
How are customer service and support?
I've never interacted with BigQuery support.
Which solution did I use previously and why did I switch?
We used Redshift as a database for our operations, but now, we've moved to BigQuery because BigQuery is much more than a database. It has more features than Redshift, and we hope to pay less than what we paid when we were using Redshift because Redshift required us to pay ahead each month, and the total cost was too much.
How was the initial setup?
BigQuery was easy to set up, but you'll need to learn how to do it. In general, the initial setup is straightforward.
I'd rate the BigQuery setup as eight out of ten.
What about the implementation team?
Our in-house team implemented BigQuery for the company.
What's my experience with pricing, setup cost, and licensing?
BigQuery pricing can increase quickly. It's a high-priced solution.
It would help if you researched how to reduce the price. It would take some time to find out how to set up BigQuery in a way that reduces its pricing.
What other advice do I have?
My company is using a data warehouse solution called BigQuery.
My advice to anyone deciding on using BigQuery is to be aware of the pricing mechanism and have a better understanding of it to avoid surprises. You pay for what you use, so it could be very easy to lose control, which means the BigQuery costs could go up fast.
I'd rate BigQuery as nine out of ten.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Data Engineering and AI Intern at .3Lines Venture Capital
Good solution for large databases that require a lot of analytics
Pros and Cons
- "BigQuery is a powerful tool for managing and analyzing large datasets. The versatility of BigQuery extends to its compatibility with external data visualization tools like Power BI and Tableau. This means you not only get query results but can also seamlessly integrate and visualize your data for better insights."
- "Some of the queries are complex and difficult to understand."
What is our primary use case?
BigQuery is a powerful tool for managing and analyzing large datasets. The versatility of BigQuery extends to its compatibility with external data visualization tools like Power BI and Tableau. This means you not only get query results but can also seamlessly integrate and visualize your data for better insights.
What is most valuable?
The product's most valuable feature is its ability to connect to visualization tools.
What needs improvement?
Some of the queries are complex and difficult to understand.
For how long have I used the solution?
I have been using the product for more than a year.
What do I think about the scalability of the solution?
My company has 100 users for BigQuery.
How are customer service and support?
The tool's support is fast to respond.
How would you rate customer service and support?
Positive
How was the initial setup?
The tool's deployment is easy if you follow Google's documentation.
What other advice do I have?
If you have a big database and lots of analytics, BigQuery is a really good tool. It helps save and manage your queries and gives you results you can show clients and others. I rate it a nine out of ten.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Buyer's Guide
Download our free BigQuery Report and get advice and tips from experienced pros
sharing their opinions.
Updated: February 2025
Product Categories
Cloud Data WarehousePopular Comparisons
Azure Data Factory
Snowflake
Teradata
Microsoft Azure Synapse Analytics
Vertica
Dremio
AWS Lake Formation
Oracle Autonomous Data Warehouse
SAP Business Warehouse
Yellowbrick Cloud Data Warehouse
Buyer's Guide
Download our free BigQuery Report and get advice and tips from experienced pros
sharing their opinions.
Quick Links
Learn More: Questions:
- Which ETL or Data Integration tool goes the best with Amazon Redshift?
- What are the main differences between Data Lake and Data Warehouse?
- What are the benefits of having separate layers or a dedicated schema for each layer in ETL?
- What are the key reasons for choosing Snowflake as a data lake over other data lake solutions?
- Are there any general guidelines to allocate table space quota to different layers in ETL?
- What cloud data warehouse solution do you recommend?
- Can you please help me understand cloud databases?
- When evaluating Cloud Data Warehouse, what aspect do you think is the most important to look for?
- bitmap index as preferred choice in data warehousing environment
- Why do you recommend using a cloud data warehouse?