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 5000 Synapse Commit Units (SCUs)
SAP Business Data Cloud
Score8.5 out of 10
N/A
SAP Business Data Cloud is a fully managed SaaS solution that unifies and governs all SAP data and seamlessly connects with third-party data—giving line-of-business leaders context to make even more impactful decisions.
It's well suited for large, fastly growing, and frequently changing data warehouses (e.g., in startups). It's also suited for companies that want a single, relatively easy-to-use, centralized cloud service for all their data needs. Larger, more structured organizations could still benefit from this service by using Synapse Dedicated SQL Pools, knowing that costs will be much higher than other solutions. I think this product is not suited for smaller, simpler workloads (where an Azure SQL Database and a Data Factory could be enough) or very large scenarios, where it may be better to build custom infrastructure.
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Scenarios of providing SAP data to external sources and to build SAP agents with Joule. SAP Business Data Cloud can turn you S/4 data into products that can then be easily shared and consumed by other tools. Specifically we've been able to create derived data products that was shared through SAP Business Data Cloud connect to databricks to be leveraged in Genie and Genie Code for agent build.
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Quick to return data. Queries in a SQL data warehouse architecture tend to return data much more quickly than a OLTP setup. Especially with columnar indexes.
Ability to manage extremely large SQL tables. Our databases contain billions of records. This would be unwieldy without a proper SQL datawarehouse
Backup and replication. Because we're already using SQL, moving the data to a datawarehouse makes it easier to manage as our users are already familiar with SQL.
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We have created the semantically rich dataproducts which are residing in the object store. We use the same dataproduct for the dashboarding and for the external non-SAP demand planning tool (maestro). This ensures data uniformity and a single source of truth.
We implemented the Capex planning model in SAP Business Data Cloud's SAC tool. Here, we could fetch the realtime data from the S4 source system and write back the planning data to the same source system via the SAP Datasphere using the seamless planning option.
An AI core model has been deployed in SAP Business Data Cloud for the service cloud V2 data. This trained model will identify the potential customers from the opportunities and automatically propose the quotation with higher accuracy.
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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
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
In the new analytics world, BDC has been a game changer for SAP Analytics. Extending the SAP data for the usage in Databricks, snow flake, GCP has opened new doors for Analytics . Shift from traditional data warehousing to Business Data fabric adapting to the change in the analytics world is the need of the hour and Sap has managed to pulled it off with BDC
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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.
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For me, since its fully cloud solution (SaaS), the prices comes based on the usage, also SAP Business Data Cloud comes with multiple service (SAP BW, SAC & Datasphere) in Single platform where the maintenance is also less, also it is already available with AI capabilities (SAP Joule), with one single platform (with multiple services) skills can be increased, having worked 13 years in SAP BW, I would like to see the evolution of the data.
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SAP Business Data Cloud has been highly available and reliable for our day-to-day activities. We have experienced very few disruptions, and the platform generally performs consistently. The reason for not awarding a perfect score is that occasional maintenance activities or cloud service issues can occur, as is common with any enterprise SaaS platform. Overall, availability has met our business needs very well.
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SAP Business Data Cloud provides solid overall performance, with pages and standard reports generally loading within an acceptable timeframe. The platform handles enterprise-scale data and analytics workloads effectively. While very large datasets, complex reports, or extensive integrations can occasionally impact response times, overall performance has been reliable and suitable for business operations.
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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.
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support team is generally responsive and knowledgeable, and most issues are addressed within acceptable timelines. Documentation and standard guidance are helpful for common scenarios.
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It will be more effective. Higher Engagement and Focus. we can ask questions and get the clarity on the spot. Better Knowledge Retention. Stronger Collaboration and Networking. Overall it will be a rich Communication. Sensitive or complex topics are often easier to discuss in person. Informal discussions during breaks often lead to valuable knowledge sharing.
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One of the best training session I attended and they covered most of the topics and answered all our questions. participants joined from different regions, infact they all had a different questions and it was different thoughts from all of then and helped to learn better. Though I was on travel, I could able yo attend the session.
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I have done implementation of models in traditional bw and Using BDC. The integration of BDC with S4 hana for creating sap data products is seamless and reduces lot of implementation effort. The intelligent app feature is BDC also eases the implementation effort. If i have to compare the previous world with new BDC, implementation effort is largely saved
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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 account computation and storage.
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When I used Collibra, it was providing good insight and automatic report but Collibra was hard to integrate with other system and required expert knowledge and Collibra team support to integrate fully. When we switched to SAP Business Data Cloud, Integration was seamless with Edna and other data storages like data lake.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
I would rate the contract terms and pricing structure of SAP Business Data Cloud as 7 out of 10. The pricing model is generally aligned with enterprise-scale deployments and provides flexibility for organizations looking to consolidate data, analytics, and governance capabilities on a single platform. The contract terms are comprehensive, and SAP offers multiple licensing options to support different business requirements and growth scenarios.The primary reason for this rating is that the pricing and licensing structure can be complex to understand, particularly when estimating long-term costs as data volumes, users, and workloads increase. Greater transparency around consumption-based charges, usage forecasting, and future scaling costs would make planning easier. I would also prefer simpler licensing bundles and more predictable pricing tiers. Overall, the model supports enterprise needs well, but additional simplicity and clarity would improve the customer experience and make budgeting more straightforward.
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SAP Business Data Cloud provides strong scalability for enterprise data management and analytics, supporting growth in data volumes, users, and business use cases. The platform's extensibility and integration capabilities make it adaptable across departments and sites. The reason I did not rate it higher is that large-scale deployments may require additional effort around governance, integration, and advanced customization to fully realize enterprise-wide adoption
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The professional services team demonstrated strong technical expertise and a solid understanding of data integration, analytics, governance, and cloud architecture. They provided valuable guidance during planning, implementation, and configuration phases, helping accelerate deployment and reduce potential risks. Their recommendations aligned well with best practices and supported a smooth transition to the platform.The reason I did not assign a higher rating is that some specialized requirements required additional consultation cycles and coordination between different teams, which occasionally extended timelines. In certain cases, deeper industry-specific examples or more tailored implementation guidance would have been beneficial. Despite these challenges, the team remained responsive, collaborative, and focused on achieving business outcomes. Overall, the professional services engagement added significant value and helped maximize the benefits of the SAP Business Data Cloud investment.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Licensing fees is replaced with Azure subscription fee. No big saving there
More visibility into the Azure usage and cost
It can be used a hot storage and old data can be archived to data lake. Real time data integration is possible via external tables and Microsoft Power BI
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With the support for AI/ML use cases via SAP Data bricks and via zero copy delta share to enterprise data bricks, it has really made a bigger impact since this was our bigger pain point with the legacy warehouse solution
With the working capital intelligent app, it was the biggest game changer and it really made big impact on the customer to understand the SAP Business Data Cloud and its capabilities
with public cloud Saas , it has reduced the maintenance effort from IT to the greater extend. With traditional BW, IT has to take the overhead of database upgrade , patch upgrade, service pack upgrade etc. This is one of the key capabilities that provides high ROI in my opinion
with the support for the zero-copy delta share to other products like snowflake and google analytics, i think we are moving towards the good direction and i think the best-selling point to the customer
With the replication flow capabilities of datasphere which is also part of SAP Business Data Cloud, it resolves another main business problem of data transfer from S4 to Microsoft fabric.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
