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 TV is well suited for high speed, which is a great for large tables. The workload functionality is very good when in Viewpoint. The BAR functionality could use a little work. QueryGrid is very useful as well. The client handlers are still a work in progress, as I keep hearing that they continue to fail. There are also many restarts on the systems as well.
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 ETL (Extract - Transfor - Load) NOS to send data from Teradata Vantage to S3 and from S3 to Teradata Vantage Teradata GeoSpacial feature Bulk reading and writing in huge tables MPP capacity already mature Temporal Capacity more mature that other solutions TASM 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 Teradata is an excellent option but only for a massive amount of data warehousing or analysis. If your data is not that big then it could be a misfit for your company and cost you a lot. The cost associated is quite extensive as compared to some other alternative RDBMS systems available in the market. Migration of data from Teradata to some other RDBMS systems is quite painful as the transition is not that smooth and you need to follow many steps and even if one of them fails. You need to start from the beginning almost. Last but not least the UI is pretty outdated and needs a revamp. Though it is simple, it needs to be presented in a much better way and more advanced options need to bee presented on the front page itself. 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 Teradata is a mature RDBMS system that expands its functionality towards the current cloud capabilities like object storage and flexible compute scale.
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 It has helped our project to save time, effort and give accurate results in the quickest possible time. The diagnostics feature is also outstanding giving us a detailed report of the error which occurred, when it occurred and the likely cause and resolution of the same as well. The support of SQL is inherited which makes it easy to work on it because you don't need to learn any new language for this.
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 We have meetings at the beginning with the technical team to explain our requirements to them and they were really putting in a lot of effort to come up with a solution which will address all our needs. They implemented the software and also trained a few of our resources on the same too. We can get in touch with them now as well whenever we run into a roadblock but it's very less now.
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 Teradata is way ahead of its competitor because of its unique features of ensuring data privacy and data never gets corrupted even in worst case scenario. In most cases, the data corruption is a major issue if left unused and it leads to important data being wiped off which in ideal case should be stored for 3 years
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 Saving time and cost through its stable integration tools which helps import and export a huge amount of different data. Providing analytics for the different data is easy and quick. Securing all the data processes across the entire company. Great Cloud solution for effective data quality management. Read full review ScreenShots Google BigQuery Screenshots Teradata Vantage Screenshots