Google BigQuery vs. SAP Business Warehouse

Google BigQuery is great for being the central datastore and entry point of data if you're on GCP. It seamlessly integrates with other Google products, meaning you can ingest data from other Google products with ease and little technical knowledge, and all of it is near real-time. Being serverless, BigQuery will scale with you, which means you don't have to worry about contention or spikes in demand/storage. This can, however, mean your costs can run away quickly or mount up at short notice.

Incentivized

SAP BW is best for: 1. Large enterprises 2. Enterprises with 3+ legacy systems with entrenched users (politically difficult to merge) 3. Enterprises with employees who can understand both the technical capabilities of SAP BW and the needs of the business users - ability to speak both languages, otherwise the program could be unwieldy and potentially underutilized (it's not particularly inexpensive) SAP BW is less appropriate for: 1. Small enterprises 2. Enterprises who have well established, same location, CRM and UFS - the integration of data analysis will be easier and less expensive with other solutions 3. HANA

Incentivized

• 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.

Incentivized

• ETL, great at taking data from OLTP source, flat file, etc... Easy drag and drop for transformations.
• Great reporting possibilities, easy to connect with BO, BPC, etc...
• Great Master Data Management (MDM )for BPC - helps us maintain master data for BPC.

Incentivized

• 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.

Incentivized

• Age of software is showing as it struggles with very large data modules, which were not as prevalent in its early years
• Querying performance at times can be very slow
• Support and development for BEx has been discontinued or hard to find.

Incentivized

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.

Incentivized

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

It needs minimal trainings and can perform tasks of data management and reporting.

Incentivized

I have never had any significant issues with Google Big Query. It always seems to be up and running properly when I need it. I cannot recall any times where I received any kind of application errors or unplanned outages. If there were any they were resolved quickly by my IT team so I didn't notice them.

Incentivized

I think Google Big Query's performance is in the acceptable range. Sometimes larger datasets are somewhat sluggish to load but for most of our applications it performs at a reasonable speed. We do have some reports that include a lot of complex calculations and others that run on granular store level data that so sometimes take a bit longer to load which can be frustrating.

Incentivized

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.

Incentivized

Google BigQuery of course collects a much much larger array of raw data and can handle (practically) an unlimited amount of data. For a large enterprise like ours that relies on large-scale analytics, this is absolutely imperative. Google BigQuery can also combine GA4 data with external sources (like CRM tools), so our analytics can be unified. Due to our heavy reliance on GA4, Google BigQuery is the natural choice since it is a Google product and has better integration.

Incentivized

SAP Business Warehouse scores higher in data warehouse functionalities for integration to SAP ERP and other SAP solutions such as SAP CRM, SAP APO, and SAP SRM. Standard SAP data source extractors which are available in SAP ERP can be used immediately for full or delta replication into SAP Business Warehouse. System governance in SAP Business Warehouse is top-notch with change management support for migration between system landscape from the development system to production system.

Incentivized

We have continued to expand out use of Google Big Query over the years. I'd say its flexibility and scalability is actually quite good. It also integrates well with other tools like Tableau and Power BI. It has served the needs of multiple data sources across multiple departments within my company.

Incentivized

• In some places, Google BigQuery has helped us save some money by avoiding the need for expensive infrastructure and reducing some of the operational costs.
• Scalability is up-to-date and really helpful in multiple places.
• Knowledge transfer is easy as it is very user-friendly, so the learning curve has been reduced.
• Also, it gives us more insights from our data, helping us make smarter decisions for our business.

Incentivized

• It has helped cut down on parts shortages with the minimum stock flags.
• People are able to track down parts easier because they can see where they were last used.
• Our sales team has better visibility on lead times so they can accurately quote our customers.

Incentivized