BigQuery vs VMware Tanzu Data Solutions comparison

"It has a proprietary way of storing and accessing data in its own data store and is 100% managed without you needing to install anything. There is no need to arrange for any infrastructure to be able to use this solution."

"The initial setup is straightforward."

"It has a well-structured suite of complimentary tools for data integration and so forth."

"The product is serverless. We only need to write SQL queries to analyze the data. We need to pay based on the number of queries. The retrieval time is very less. Even if you write large queries, the tool is able to bring back data in a few seconds."

"The feature called calibrating the capacity is 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."

"Even non-coders can review the data in BigQuery."

"BigQuery can be used for any type of company. It has the capability of building applications and storing data. It can be used for OLTP or OLAP. It has many other products within the Google space."

"I like the high throughput of 20K messages/sec, and that it supports multiple protocols."

"With VMware Tanzu Greenplum, one can make a huge database table and analyze the queries by adding in the SQL command. Some hint or command for the query goes over the multi-parallel execution."

"The most valuable feature for me is that it is open source. The licensing costs are really low and they are transparent."

"Pivotal Greenplum's shared-nothing architecture."

"The product's reliability is the most valuable feature."

"After creating a RabbitMQ service, they provide you with a sort of web management dashboard."

"Scalability is simple because it's an MPP database. If you need more processing power or you need more storage, you just add a few more nodes in the cluster. It works on common commodity hardware. You can use any type of server. You don't need to have proprietary hardware. It's fairly flexible."

"The loading speed is very good."

"There are some limitations in the query latency compared to what it was three years ago."

"The processing capability can be an area of improvement."

"It would be helpful if they could provide some dashboards where you can easily view charts and information."

"We would like to be able to calibrate the solution to run on top of a raw file."

"When I execute a query, the dashboard doesn't always present the output seamlessly. Troubleshooting requires opening each pipeline individually, which is time-consuming."

"It would be better if BigQuery didn't 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. But in BigQuery, we have huge restrictions. If we have some symbols, like a hash or other special characters, it won't accept them. Not in all cases, but it won't accept a few special characters, and when we migrate, we get errors. We need to use Regexp or something similar to replace that with another character. This isn't expected from a high-range technology like BigQuery. It has to adapt all products. For instance, if we have a TV Showroom, the TV symbol will be there in the shop name. Teradata and Apache Spark accept this, but BigQuery won't. This is the primary concern that we had. In the next release, it would be better if the query on the external table also had cache. Right now, we are using a GCS bucket, and in the native table, we have cache. For example, if we query the same table, it won't cost because it will try to fetch the records from the cached result. But when we run queries on the external table a number of times, it won't be cached. That's a major drawback of BigQuery. Only the native table has the cache option, and the external table doesn't. If there is an option to have an external table for cache purposes, it'll be a significant advantage for our organization."

"It would be beneficial to integrate additional tools, particularly from a business intelligence perspective."

"There is a good amount of documentation out there, but they're consistently making changes to the platform, and, like, their literature hasn't been updated on some plans."

"Some integration with other platforms like design tools, and ETL development tools, that will enable some advanced functionality, like fully down processing, etc."

"The solution needs improvement on performance."

"I saw some limitation with respect to the column store, and removing this would be an improvement."

"I was struggling with installing a few things. It would be good if was somewhat similar to RedHat. There should be more documentation regarding installation troubleshooting."

"they need to interact more with customers. They need to explain the features, especially when there are new releases of Greenplum. I know just from information I've found that it has other features, it can be used to for analytics, for integration with Big Data, Hadoop. They need to focus on this part with the customer."

"The fact that a single queue can't be distributed across multiple instances/nodes is a major disadvantage."

"It will be very useful if we could communicate with other database types from Greenplum (using a database link)."

"I’d like this dashboard to use web sockets, so it would actually be in real time. It would slightly increase debugging, etc."

"The price could be better. Usually, you need to buy the license for a year. Whenever you want more, you can subscribe to it, and you can use it. Otherwise, you can terminate the license. You can use it daily or monthly, and we use it based on a project's requirements."

"The pricing appears to be competitive for the intended usage scenarios we have in mind."

"BigQuery is inexpensive."

"Its cost structure operates on a pay-as-you-go model."

"Price-wise, I think that is very reasonable."

"The platform is inexpensive."

"The solution is pretty affordable and quite cheap in comparison to PDP or Cloudera."

"I have tried my own setup using my Gmail ID, and I think it had a $300 limit for free for a new user. That's what Google is offering, and we can register and create a project."

"The solution's pricing is cost-effective as it does not involve significant expenses. Licensing is required only for the server, while clients do not need any licensing. Therefore, it proves to be a cost-efficient option."

"The pricing for RabbitMQ is reasonable. It is worth the cost."

"It is the best product with best fit for price/performance customer objectives."

"It is an open-source product."

"The product is available for free use since it is an open-source technology."

"This is an open source solution."

"On a scale of one to five, with five being the most competitive pricing, I would rate this solution as a four."

"Since the tool is an open-source product, there is no need to pay anything."