Azure Synapse Analytics is described as the former Azure SQL Data Warehouse, evolved, and as a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives users the freedom to query data using either serverless or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.
$4,700
per month 5,000 Synapse Commit Units (SCUs)
SAP BW/4HANA
Score 8.0 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,…
N/A
Pricing
Azure Synapse Analytics
SAP BW/4HANA
Editions & Modules
Tier 1
$4,700
per month 5,000 Synapse Commit Units (SCUs)
Tier 2
$9,200
per month 10,000 Synapse Commit Units (SCUs)
Tier 3
$21,360
per month 24,000 Synapse Commit Units (SCUs)
Tier 4
$50,400
per month 60,000 Synapse Commit Units (SCUs)
Tier 5
$117,000
per month 150,000 Synapse Commit Units (SCUs)
Tier 6
$259,200
per month 360,000 Synapse Commit Units (SCUs)
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Offerings
Pricing Offerings
Azure Synapse Analytics
SAP BW/4HANA
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
Optional
Additional Details
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More Pricing Information
Community Pulse
Azure Synapse Analytics
SAP BW/4HANA
Considered Both Products
Azure Synapse Analytics
Verified User
Anonymous
Chose Azure Synapse Analytics
They're all part of the Microsoft Azure family, so they are not exactly competitors. They overlap in functionality, but they're targeted at different levels of customers. Azure Data Factory is an excellent stand-alone PaaS (included in Synapse Analytics) for writing, scheduling, …
When client is already having or using Azure then it’s wise to go with Synapse rather than using Snowflake. We got a lot of help from Microsoft consultants and Microsoft partners while implementing our EDW via Synapse and support is easily available via Microsoft resources and …
In comparing Azure Synapse to the Google BigQuery - the biggest highlight that I'd like to bring forward is Azure Synapse SQL leverages a scale-out architecture in order to distribute computational processing of data across multiple nodes whereas Google BigQuery only takes into …
Director, eCommerce Analytics and Digital Marketing
Chose Azure Synapse Analytics
Azure Synapse Analytics stacks up well against the competitors I mentioned above. Technically, Azure SQL Datawarehouse is an upgraded version of the Azure SQL Database. So, the choice to move from one to the other depends on the processing needs of your company. If you need …
We also looked at Oracle Data Warehouse as part of our short list of products to implement as a solution. Oracle's product turned out to have less support by way of easily accessible internet blogs. Oracle was also considerably more expensive and we would have needed to hire …
SQL Data Warehousing is much easier to manage if you already have SQL Server experience and analysts who are familiar with its interface. We are currently piloting using NoSQL and Hadoop type databases but it is difficult to get set up properly. Additionally, we have to …
Synapse, in comparison has its ups and downs against the competitors. However, where it excels, and builds it's markets is the cheaper costs (compared to Redshift), low code platforms and an in house solution that does not need you to leave the Synapse workspace for end to end …
Databricks is a complete product with new features constantly coming out. This can be both good or bad, with a lot of innovation comes a responsibility to keep your code and pipelines fresh.
Our team evaluated multiple platform as I mentioned above , but we stacks up Azure Synapse Analytics because : 1. Easy UI and Unified platform advantage 2. Tight integrations with MS ecosystem.
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 …
Both are comparable with the advantage going to BW for SAP integration, simplified data modeling, and overall performance. Both play a key part in our overall data warehousing strategy and are complementary based on each of their strengths specific to data provisioning, and …
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. …
Unfortunately I never had the chance to work with other tools similar to SAP BW/4HANA. In the different companies I've worked for during the past 4 years, they all used SAP, and in particular I worked in SAP BW during the last year.
We used to have QlikView reporting some years ago. It was very user-friendly but when you needed some kind of data that was not considered by the solution creator, you needed to pay a developer for that need. SAP BW/4HANA needs very little customisation to offer you new data …
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 …
In terms of a well-suited scenario - the Azure Synapse can be used to capture data from multiple sources (especially from onPrem sources apart from Dataverse) and update the transformed data based on the given conditions (eg: refresh data based on the specified date/time ranges). Also, the transformed data can simply be transferred to Azure Data Lake for further processing by utilizing other analytics tools such as PowerBI.
Solid data warehouse based on best-in-class in-memory HANA database with excellent integration into SAP solutions, as well as predelivered business content facilitating initial implementation. Leverages the best of SAP's architecture and flexible data warehousing capabilities, without compromising performance and simplification. Will be key enabler to our Finance and HCM analytics roadmap.
Keeping things "complicated, but simple"; [heterogeneous] data formats seen as just SQL tables to business experts used to use Power BI, Excel, and any other traditional SQL-oriented BI tools
Integration options using "Synapse pipelines", the application of ADFs
The greatly integrated solution of independent things (Spark MPP cluster, MPP SQL Servers, ADFs) - all sitting under one roof. Great job!
Integration with super-fast, globally replicated data. I really appreciate the integration of NoSQL databases (namely Core API and Mongo API under Cosmos DB) with purely batch-processed BI data
With Azure, it's always the same issue, too many moving parts doing similar things with no specialisation. ADF, Fabric Data Factory and Synapse pipeline serve the same purpose. Same goes for Fabric Warehouse and Synapse SQL pools.
Could do better with serverless workloads considering the competition from databricks and its own fabric warehouse
Synapse pipelines is a replica of Azure Data Factory with no tight integration with Synapse and to a surprise, with missing features from ADF. Integration of warehouse can be improved with in environment ETl tools
The data warehouse portion is very much like old style on-prem SQL server, so most SQL skills one has mastered carry over easily. Azure Data Factory has an easy drag and drop system which allows quick building of pipelines with minimal coding. The Spark portion is the only really complex portion, but if there's an in-house python expert, then the Spark portion is also quiet useable.
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.
Microsoft does its best to support Synapse. More and more articles are being added to the documentation, providing more useful information on best utilizing its features. The examples provided work well for basic knowledge, but more complex examples should be added to further assist in discovering the vast abilities that the system has.
I never experienced any support issue when using SAP BW/4HANA. The only issues I faced were at the moment of installing the tool in my computer but I got support from the local IT department of my company and was quickly fixed
They're all part of the Microsoft Azure family, so they are not exactly competitors. They overlap in functionality, but they're targeted at different levels of customers. Azure Data Factory is an excellent stand-alone PaaS (included in Synapse Analytics) for writing, scheduling, and monitoring pipelines. Azure SQL Database (and all the Azure SQL family) is excellent for traditional, SQL-based data warehouses, especially if you're migrating from on-premises. Combined with Azure Data Factory (that can run SSIS packages), it's a perfect solution for a simple path to the cloud. Azure Databricks is effectively the only internal "competitor" to Synapse Analytics but targeted more to a "platform-agnostic" audience. On the other hand, Synapse is more of a proprietary mix of products that are more tightly related to Microsoft technologies.
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.
It definitely has a positive impact on ROI. We are able to use it to generate MORE revenue through predictive analytics and pricing optimization.
Because of the SQL Data Warehouse design, we're able to set up some self service reporting tools which allow our users to generate reports ad hoc instead of having a full time employee creating these by hand.
Having visibility into the data is very useful for management to make good business decisions.