Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.
$6.25
per TiB (after the 1st 1 TiB per month, which is free)
SAP BW/4HANA
Score 8.1 out of 10
N/A
SAP BW/4HANA is a next-generation
data warehouse solution. It is specifically designed to use the advanced
in-memory capabilities of the SAP HANA platform. For example, SAP BW/HANA can
integrate many different data sources to provide a single, logical view of all
the data. This could include data contained in SAP and non-SAP applications
running on-premise or in the cloud, and data lakes, such as those contained in
the Apache Hadoop open-source software framework. With SAP BW/4HANA,…
We use a mix of different tools, primarily Snowflake and SAP BW/4HANA - the first as our main Data Lake and integrated with other reporting and visualization tools, and the second as the main source of BI/Reporting into the ERP layer - Operations, Logistics, Inventory, Finance. …
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.
Some scenarios where SAP BW/4HANA is well suited are retail industry, supply chain, finance, warehouse, stocking processes, BI, [and] some finance analytics reporting. Some scenarios where SAP BW/4HANA is less appropriate [is when] relational queries are needed [and] in some small business with infrastructure limitations. Another scenario that is less appropriate is for ABAP processes requirements.
First and foremost - Google BigQuery is great at quickly analyzing large amounts of data, which helps us understand things like customer behavior or product performance without waiting for a long time.
It is very easy to use. Anyone in our team can easily ask questions about our data using simple language, like asking ChatGPT a question. This means everyone can find important information from our data without needing to be a data expert.
It plays nicely with other tools we use, so we can seamlessly connect it with things like Google Cloud Storage for storing data or Data Studio for creating visual reports. This makes our work smoother and helps us collaborate better across different tasks.
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.
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.
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
SAP BW/4HANA requires specialized skillsets around data warehouse modeling and the access to data, however the modeling capabilities are intuitive and have now become accessible to both SAP and non-SAP data warehouse specialists. This new model allows for Interchangeable skillsets and access to a broader pool of experts throughout the industry, as well as easier access to data.
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.
SAP Max Attention and general support for SAP BW/4HANA is broadly available. Truth to be told, MaxAttention has a premium cost but brings great engineers. So this being an enterprise capability and extremely critical, we did not consider cost as the main factor since support works well. Just keep that in mind when making your selection.
PowerBI can connect to GA4 for example but the data processing is more complicated and it takes longer to create dashboards. Azure is great once the data import has been configured but it's not an easy task for small businesses as it is with BigQuery.
SAP Analytics Cloud is complemented by SAP BW/4 HANA through connectors that work in real-time and allow the display of indicator information in interactive and user-friendly visualizations. SAP Data Services integrates with BW/4 HANA allowing to automate the loading of information in the system taking as a data source a wide variety of platforms.
Google Support has kindly provide individual support and consultants to assist with the integration work. In the circumstance where the consultants are not present to support with the work, Google Support Helpline will always be available to answer to the queries without having to wait for more than 3 days.
Previously, running complex queries on our on-premise data warehouse could take hours. Google BigQuery processes the same queries in minutes. We estimate it saves our team at least 25% of their time.
We can target our marketing campaigns very easily and understand our customer behaviour. It lets us personalize marketing campaigns and product recommendations and experience at least a 20% improvement in overall campaign performance.
Now, we only pay for the resources we use. Saved $1 million annually on data infrastructure and data storage costs compared to our previous solution.
