Likelihood to Recommend It is easy to set up, and within 10 minutes it is up and running. You can add many domains in one dashboard. So no need for a separate Cloudflare account. I can access all my domain DNS, and customize/add it further. For example by adding the Google Webmaster DNS key or my email provider.
Read full review 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 Pros Registrar and DNS services are impeccable, with registrations done at cost and without ADs. DNS services setting standards for speed of resolution. DDOS protection. With their content distribution network to back them they have the bandwidth and tools to be both proactive and reactive to bad actors. WAF - Their Web Application Firewall helps mitigate common site vulnerabilities and has active zero-day protection running for breaking exploits Read full review 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 Cons In some cases, using Cloudflare can actually lead to slower website speeds if the network is congested or if the website's traffic is particularly heavy. Some website owners may find that the level of customization offered by Cloudflare is limited, especially in comparison to other solutions. While Cloudflare is easy to set up and manage, it may be too complex for users who are not familiar with web technologies. Read full review 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 Likelihood to Renew lower cost
Read full review 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 Usability Everything is extremely concise and all settings apply immediately and take effect globally. There is no reason to explicitly plan/think in terms of individual regions as one would have to traditional cloud offerings (AWS, OCI, Azure). All Cloudflare products integrate seamless as part of a single pipeline that executes from request to response.
Read full review 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 Reliability and Availability In 6+ years of relying on Cloudflare, I think we experienced one or two brief outages that were Cloudflare's fault.
Read full review Performance Their Argo for the global network is the core feature we love.
Read full review Support Rating We really like to talk to a person on the phone or using chat. But the system is very slow and sending to much email to get the issue solve. Something we don't like to spend time writing on the community forum our issue because we don't want to share detail information of our POC.
Read full review 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 Implementation Rating Very well executed implementation where our team was able to handle the implementation with guidance.
Read full review Alternatives Considered Firebase can be a good starter for basic projects but as I scaled up, I found it lacking the maturity Cloudflare has. Naturaly, I opted for Cloudflare for bigger projects. I still use
Firebase , but for small scale hobby projects only.
Read full review 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 Contract Terms and Pricing Model None so far. Very satisfied with the transparency on contract terms and pricing model.
Read full review Scalability They are built for scale and have the capacity to handle all the traffic we could ever expect to get.
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 A lot of requests are cached and so egress costs from downstream providers are mitigated. DDoS protection has also managed to keep our site up and our cloud computing bill down. Setting up a proxy with a worker made putting various Google Cloud Functions running behind a single URL very easy and performant. Plus they offer API Shield on top of this. Read full review 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 ScreenShots Google BigQuery Screenshots