Databricks Data Intelligence Platform vs. SAP BW/4HANA

Medium to Large data throughput shops will benefit the most from Databricks Spark processing. Smaller use cases may find the barrier to entry a bit too high for casual use cases. Some of the overhead to kicking off a Spark compute job can actually lead to your workloads taking longer, but past a certain point the performance returns cannot be beat.

Incentivized

SAP BW/4HANA is certainly an excellent choice when it comes to setting up a data warehousing platform within a landscape of existing SAP systems ecosystem for realizing quick time to value and ROI over the long term. Many non-SAP analytics tools such as Power BI , Qlik also now offer connectors to leverage SAP BW/4HANA data as additional options to deploy third party visualization tools which make it a more open ended platform of choice. But with the future roadmap of SAP and industry in general being focused towards cloud based offerings (SAC and Datasphere) infused with AI capabilities one has to make a judicious choice among these depending on the use case, capabilities of platforms and existing systems landscape and the overall long term IT strategy. SAP BW/4HANA may not be a good platform of choice if starting a native greenfield data warehousing implementation with cloud first approach which would require data integration across SAP and Non-SAP sources and one should consider other SAP cloud offerings which however still have some time to reach a level of maturity as SAP BW/4HANA has reached over the years.

Incentivized

• Process raw data in One Lake (S3) env to relational tables and views
• Share notebooks with our business analysts so that they can use the queries and generate value out of the data
• Try out PySpark and Spark SQL queries on raw data before using them in our Spark jobs
• Modern day ETL operations made easy using Databricks. Provide access mechanism for different set of customers

Incentivized

• With ODP based extraction, SAP BW/4HANA does well to integrate the data from various source systems like S4HANA , S4C.
• With composite providers having the ability to integrate HANA calculation views, we are able to make the best of use of both application layer and data base layer(HANA) for mixed modelling scenarios.
• with data tiering optimization higher data volume are effectively handled as we have the option to control the amount of data that is being stored in HOT , Warm and cold storage. With data volume grows over the year, DTO comes in handy solution to automatically move the delta to appropriate area based on temporature.

Incentivized

• Sometimes, when multiple jobs depend on each other in different environments, it is not always easy to see the full workflow in one place.
• It is sometimes difficult to determine which job or cluster contributes more to the overall cost.
• For beginners, cluster configuration may be a little difficult. So more recommendation in the platform can help.

Incentivized

• Better integration with HANA layer with BW/4HANA application
• Flexibility to provide more secure API's to interact with non-sap Data bases
• Integration with Gsheets as well like Excel(AFO) and introduce better reporting integration with various reporting tools.
• Evolution to provide better data lake , data brick options like in BDC

Incentivized

Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.

in terms of graph generation and interaction it could improve their UI and UX

Incentivized

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.

Incentivized

One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.

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.

Incentivized

The most important differentiating factor for Databricks Lakehouse Platform from these other platforms is support for ACID transactions and the time travel feature. Also, native integration with managed MLflow is a plus. EMR, Cloudera, and Hortonworks are not as optimized when it comes to Spark Job Execution. Other platforms need to be self-managed, which is another huge hassle.

Incentivized

SAP BW / 4HANA and SAP IQ are both used for warehouse; with quick consultations for business analysis and that allows us to obtain dashboards and KPIs efficiently. SAP IQ is columnar and SAP BW / 4HANA immemorial. SAP BW / 4HANA was selected for the response speed of the queries since it saves the information in cache.

Incentivized

• The ability to spin up a BIG Data platform with little infrastructure overhead allows us to focus on business value not admin
• DB has the ability to terminate/time out instances which helps manage cost.
• The ability to quickly access typical hard to build data scenarios easily is a strength.

Incentivized

• SAP BW/4HANA has been immensely helpful in eliminating alternate silos of data creation by business users thereby ensuring data integrity and consistency across the organization. The focus is now more on data analysis as opposed to data preparation in spreadsheets saving users hours of laborious manual work in collating data.
• We have been able to quickly integrate and leverage data from multiple SAP systems into SAP BW/4HANA to drive holistic decision making within the organization including streamlining the month end close process using BPC.
• Excel friendly reporting tools such as Analysis for Office have made it much easier for user adoption and training making change management much easier and change the culture within the organization.

Incentivized