We performed a comparison between BigQuery and Oracle Database Appliance based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."When integrating their system into the cloud-based solutions, we were able to increase their efficiency and overall productivity twice compared with their on-premises option."
"The initial setup process is easy."
"It stands out in efficiently handling internal actions without the need for manual intervention in tasks like building cubes and defining final dimensions."
"It's similar to a Hadoop cluster, except it's managed by Google."
"The most valuable features of BigQuery is that it supports standard SQL and provides good performance."
"I like that we can synch and run a large query. I also like that we can work with a large amount of data. You don't need to work separately, as it's a ready-made solution. It also comes with a built-in machine-learning feature. Once we start inputting the data, it will suggest some things related to the data, and we can come up with nice dashboards and statistics from a vast amount of data."
"We like the machine learning features and the high-performance database engine."
"The main thing I like about BigQuery is storage. We did an on-premise BigQuery migration with trillions of records. Usually, we have to deal with insufficient storage on-premises, but in BigQuery, we don't get that because it's like cloud storage, and we can have any number of records. That is one advantage. The next major advantage is the column length. We have some limits on column length on-premises, like 10,000, and we have to design it based on that. However, with BigQuery, we don't need to design the column length at all. It will expand or shrink based on the records it's getting. I can give you a real-life example based on our migration from on-premises to GCP. There was a dimension table with a general number of records, and when we queried that on-premises, like in Apache Spark or Teradata, it took around half an hour to get those records. In BigQuery, it was instant. As it's very fast, you can get it in two or three minutes. That was very helpful for our engineers. Usually, we have to run a query on-premises and go for a break while waiting for that query to give us the results. It's not the case with BigQuery because it instantly provides results when we run it. So, that makes the work fast, it helps a lot, and it helps save a lot of time. It also has a reasonable performance rate and smart tuning. Suppose we need to perform some joins, BigQuery has a smart tuning option, and it'll tune itself and tell us the best way a query can be done in the backend. To be frank, the performance, reliability, and everything else have improved, even the downtime. Usually, on-premise servers have some downtime, but as BigQuery is multiregional, we have storage in three different locations. So, downtime is also not getting impacted. For example, if the Atlantic ocean location has some downtime, or the server is down, we can use data that is stored in Africa or somewhere else. We have three or four storage locations, and that's the main advantage."
"The initial setup was straightforward and quick - I was able to configure everything within an hour."
"The product’s valuable feature is its capability to pre-configure and pre-install the settings."
"Oracle Database Appliance is a stable solution. We have clients that have been running it for 10 years."
"The solution is pretty automated, which takes out the possibility of human error."
"We primarily use it for OLTP, which has improved our costs."
"We use the solution for our Java applications."
"The database is solid."
"Oracle Database Appliances are specifically designed for Oracle databases. They have built-in utilities and tools that simplify management, making them the best option for Oracle database management systems."
"The product’s performance could be much faster."
"There are many tools that you have to use with BigQuery that are different services also provided for by Google. They need to all be integrated into BigQuery to make the solution easier to use."
"The main challenges are in the areas of performance and cost optimizations."
"Some of the queries are complex and difficult to understand."
"I noticed recently it's more expensive now."
"As a product, BigQuery still requires a lot of maturity to accommodate other use cases and to be widely acceptable across other organizations."
"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. 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."
"The setup is a bit complex."
"They could incorporate a more secure and internet-centric management system for the platform."
"Even though the solution can handle a lot of data, it's just too expensive currently."
"Virtualization features could also be improved. A web-based GUI would be a good start."
"Technical support is not so great. It could be much better. The maintenance, for an enterprise system, isn't so great. It's also extremely expensive."
"I would like it if the scalability could be increased without having to change versions."
"The product is quite complex to set up, initially. It would be ideal if it was simpler."
"Oracle Database Appliance patching comes out two to three months after the regular patching cycle."
BigQuery is ranked 5th in Cloud Data Warehouse with 31 reviews while Oracle Database Appliance is ranked 6th in Data Warehouse with 40 reviews. BigQuery is rated 8.2, while Oracle Database Appliance is rated 8.0. The top reviewer of BigQuery writes "Expandable and easy to set up but needs more local data residency". On the other hand, the top reviewer of Oracle Database Appliance writes "Simplifies database management tasks and provides high availability and disaster recovery". BigQuery is most compared with Snowflake, Teradata, Oracle Autonomous Data Warehouse, Vertica and Apache Hadoop, whereas Oracle Database Appliance is most compared with Oracle Exadata, VMware Tanzu Greenplum, Dremio, Actian Ingres and Vertica. See our BigQuery vs. Oracle Database Appliance report.
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