We performed a comparison between BigQuery and SAP Business Warehouse 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."The initial setup process is easy."
"It's similar to a Hadoop cluster, except it's managed by Google."
"We basically used it to store server data and generate reports for enterprise architects. It was a valuable tool for our enterprise design architect."
"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."
"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."
"It's straightforward to set up."
"There are some performance features like partitioning, which you can do based on an integer, and it improves the performance a lot."
"We like the machine learning features and the high-performance database engine."
"The most valuable feature of this solution is the advanced structuring of data capabilities. You can get different structures of data to suit your needs."
"The most valuable aspect of the solution is the integration with SAP ERP."
"The most valuable feature of SAP Business Warehouse is transformation, where I extract data from different sources, particularly the raw data. Then I do some transformations and store that in a format that allows me to do reporting easily."
"The key element in this solution is its rapid response. If you have a question about prices, buyers, customers, providers, or services, you need the answer in a minute or two. That's the key benefit for us that a solution like BW gives us."
"We are currently in a basic stage of analytics and the first goal we have is to make sure the numbers are correct. BW has some features that help you to build factors and ETL in such a way that it's easy to get to correct responses. That's the number one condition that you have to have in an analytic solution."
"What I like most about SAP Business Warehouse is that it's a seamless integration platform. A valuable feature in the tool is the monitoring alert that makes you aware of what process chain has failed. There's no manual monitoring required if you have configured an alert system, so the process chain can run in the background, and you can get alerts about it. The functionalities I find good in SAP Business Warehouse are alerting and monitoring. If you have configured the tool and have integrated it with SAP Solution Manager, then it's a good product to use."
"What I like most about SAP Business Warehouse is its ability to feed data into new, multiple systems in various formats. It can open its data to any system over gateway services or a portal or application that needs to consume and analyze data."
"The most useful feature is definitely the speed."
"For greater flexibility and ease of use, it would be beneficial if BigQuery offered more third-party add-ons and connectors, particularly for databases that don't have built-in integration options."
"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 of the queries are complex and difficult to understand."
"I understand that Snowflake has made some improvements on its end to further reduce costs, so I believe BigQuery can catch up."
"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."
"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. You have to actually open a ticket and then follow it up with Google support."
"The solution should reduce its pricing."
"The price could be better. Compared to competing solutions, BigQuery is expensive. It's only suitable for enterprise customers, not small and medium-sized businesses, as they cannot afford this kind of solution. In the next release, it would be better if they improved their AI bot. Although machine learning and artificial intelligence are doing wonders, there is still a lot of room to enhance them."
"I'm not sure if our issue is related to BW or the Analysis Office. However, we're having performance issues in terms of time. It takes a long time to generate the report."
"The problem with BW, and the factor that differentiated it from the original BW, is that you only get limited functionality with your runtime license. So, you have to pay extra for extracting data."
"What I'd like improved in SAP Business Warehouse is its setup. It could be more flexible, and it could be a configuration-based setup."
"You can start quickly but, when you have to get a little more detailed, when you have to change something, when you have to solve problems, it's not that easy. It's easy to start but evolving is not that easy."
"In the next release, my suggestion would be to have user-friendly interfaces and performance issues be addressed."
"It's a product that is at the end of life so they will not improve it anymore."
"The solution could offer better connectivity with other databases."
"Areas for improvement in SAP Business Warehouse include enhancing scheduling and monitoring tools, as well as improving communication about hidden features to make them more accessible to users."
BigQuery is ranked 5th in Cloud Data Warehouse with 31 reviews while SAP Business Warehouse is ranked 8th in Cloud Data Warehouse with 25 reviews. BigQuery is rated 8.2, while SAP Business Warehouse is rated 7.8. 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 SAP Business Warehouse writes "Offers powerful analytics and integration capabilities but requires improved upgrade processes". BigQuery is most compared with Snowflake, Teradata, Oracle Autonomous Data Warehouse, Vertica and Microsoft Azure Synapse Analytics, whereas SAP Business Warehouse is most compared with Microsoft Azure Synapse Analytics, Snowflake, SAP BW4HANA, Amazon Redshift and SAP NetWeaver Business Warehouse. See our BigQuery vs. SAP Business Warehouse report.
See our list of best Cloud Data Warehouse vendors.
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