Otherwise, you can terminate the license. Whenever you want more, you can subscribe to it, and you can use it. Usually, you need to buy the license for a year. "The price is a bit high but the technology is worth it.".This is why the pricing models are different and it becomes a key consideration in the decision of which platform to use." Snowflake is costlier for one terabyte, but BigQuery charges based on how much data is inserted into the tables.īigQuery charges you based on the amount of data that you handle and not the time in which you handle it. "One terabyte of data costs $20 to $22 per month for storage on BigQuery and $25 on Snowflake.That's what Google is offering, and we can register and create a project." "I have tried my own setup using my Gmail ID, and I think it had a $300 limit for free for a new user.They need to all be integrated into BigQuery to make the solution easier to use." If there is an option to have an external table for cache purposes, it'll be a significant advantage for our organization." "There are many tools that you have to use with BigQuery that are different services also provided for by Google. Only the native table has the cache option, and the external table doesn't. But when we run queries on the external table a number of times, it won't be cached. For example, if we query the same table, it won't cost because it will try to fetch the records from the cached result. Right now, we are using a GCS bucket, and in the native table, we have cache. In the next release, it would be better if the query on the external table also had cache. Teradata and Apache Spark accept this, but BigQuery won't. For instance, if we have a TV Showroom, the TV symbol will be there in the shop name. This isn't expected from a high-range technology like BigQuery. We need to use Regexp or something similar to replace that with another character. Not in all cases, but it won't accept a few special characters, and when we migrate, we get errors. If we have some symbols, like a hash or other special characters, it won't accept them. But in BigQuery, we have huge restrictions. For example, when we migrate from on-premises to on-premise, the data which handles all ebook characters can be handled on-premise. You have to actually open a ticket and then follow it up with Google support." "So our challenge in Yemen is convincing many people to go to cloud services." "There are some limitations in the query latency compared to what it was three years ago." "It would be better if BigQuery didn't have huge restrictions. Although machine learning and artificial intelligence are doing wonders, there is still a lot of room to enhance them." "It would be helpful if they could provide some dashboards where you can easily view charts and information." "With other columnar databases like Snowflake, you can actually increase your VM size or increase your machine size, and you can buy more memory and it will start working faster, but that's not available in BigQuery. In the next release, it would be better if they improved their AI bot. It's only suitable for enterprise customers, not small and medium-sized businesses, as they cannot afford this kind of solution. Compared to competing solutions, BigQuery is expensive. "When it comes to queries or the code being executed in the data warehouse, the management of this code, like integration with the GitHub repository or the GitLab repository, is kind of complicated, and it's not so direct." "The price could be better. It allows for modifying the primary projection without altering the tables, which helps to optimize queries without the need to modify the underlying data." "Vertica's most outstanding features are the compression rates achieved and the speed of access of high volume data." Of course, it's a cluster, so it's easy to scale." "I enjoy the cybersecurity and backup features." "I appreciate the flexibility offered by Vertica's projections. Performance is good, and it can return ad hoc queries very quickly. We use Red Tool and Red Job for the data warehouse and reporting. It is very fast and has saved us a lot of money." "The feature I like best is performance. So it provides workload isolation." "The solution is quick, has good compression data, and is not expensive." "I have found the solution to be scalable." "The hardware usage and speed has been the most valuable feature of this solution. So you have low-cost object storage for primary storage and the ability to have several sub-clusters working off the same ObjectStore. From an architecture standpoint, they have separated compute and storage.
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