Business Trends
Building analogy between SAP, Microsoft, Google and Amazon cloud analytical services and tools
As more and more customers are migrating to cloud and starting to use different cloud services, there is more and more frequent situation, when it is hard to understand, whether there is already service or tool in the existing landscape, which covers a business scenario or it is necessary to buy and implement a new one.
This short blog post with only one table is aimed to draw high-level analogy between SAP, Microsoft, Google and Amazon cloud services and tools in the area of analytics.
It is important to say, that it is not a comparison or statement, what to use in which situation, but only an attempt to take a look at the current analytical enterprise needs from technology perspective, rather than from marketing.
The listed in the first column business cases, for sure, do not cover all possible big scenarios, but only main of them.
Business need | SAP | Microsoft | GCP | Amazon |
Limitless analytics service with unmatched time to insight | Data Warehouse Cloud | Azure Synapse Analytics | Cloud Data Fusion/BigQuery/Dataproc | Redshift |
Apache Spark based analytics platform | SAP HANA Cloud | Azure Databricks | BigQuery/Dataproc/Cloud Dataflow | EMR |
Fully managed cloud Hadoop and Spark service | SAP HANA Cloud | HDInsight | Dataproc | EMR |
A data integration service to orchestrate and automate data movement and transformation | Data Intelligence/BTP Integration Suite | Data Factory | Cloud Data Fusion | Data Pipeline/Glue |
Open and elastic AI development | Data Intelligence and AI Core | Azure Machine Learning | Vertex AI | SageMaker |
Real-time data stream processing | SAP Streaming Analytics | Azure Stream Analytics | Cloud Pub/Sub | Kinesis |
On-demand analytics service with enterprise-grade security, auditing, and support | Data Intelligence | Data Lake Analytics | Dataproc/BigQuery | S3 + Athena |
Enterprise grade analytics engine as a service | Data Warehouse Cloud | Azure Analysis Services | BigQuery | Kinesis |
A hyper-scale telemetry ingestion service that collects, transforms, and stores millions of events | Event Mesh | Event Hubs | Cloud Pub/Sub | Kinesis Firehose + Kinesis Streams |
Scalable data exploration service | Analytics Cloud | Azure Data Explorer | BigQuery | Amazon Timestream |
Service for sharing big data with external organizations | Data Hub | Azure Data Share | Datashare Toolkit | Lake Formation |
IoT analytics platform to monitor, analyze, and visualize industrial IoT data at scale | SAP Internet of Things | Azure Time Series Insights | BigQuery | Amazon Timestream |
Hi Alexander,
thank you for this table which is really a interesting thing and some work to put that together in the right way.
Just to sync my understanding, some questions:
I would be happy if you could show clearer definitions for this business needs. I think it is not easy to build such a table as not all offerings are comparable from the different vendors.
Thank you for further discussion.
Peter
Hello Peter,
thank you a lot for your detailed comments. I updated the table accordingly.
"Scalable data exploration service" - I changed to Analytics Cloud
With Data Hub I mean this one - would it work?
Best regards,
Alexander