MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
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SAP Business Data Cloud
Score8.6 out of 10
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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.
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Pricing
MongoDB
SAP Business Data Cloud
Editions & Modules
Shared
$0
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Serverless
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Dedicated
$57
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Pricing Offerings
MongoDB
SAP Business Data Cloud
Free Trial
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No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
Fully managed, global cloud database on AWS, Azure, and GCP
If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
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SAP Business Data Cloud is suited mainly for SAP data integration. We could able to easily consolidate the data from S4 and service cloud V2 system. SAP Business Data Cloud enables realtime data replications. We could able to leverage the AI core features. As my previous data warehousing skill is from SAP BW, I am missing some basic features comparing to BW. Master data manual maintenance, Time dependant masterdata, language independent text is also not straightforward.
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Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
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Support for AI/ML use cases with SAP Data bricks and without the need to physically transfer the data from datasphere environment.
Provide near realtime data for analytics from S4C public cloud via data products which was the primary business problem that our customers were concerned with
Provides support to use the best of both the worlds like SAP and Databricks
New releases that support for the zero-copy delta share via SAP Business Data Cloud connect to other products like snowflake, google big query and other products in roadmap
Moving towards the lakehouse architecture or similar architecture from the former warehouse architecture to meet the increasing demand for the data
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An aggregate pipeline can be a bit overwhelming as a newcomer.
There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
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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. TR verified that a representative sample of customers was invited. More Info
I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
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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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NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
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SAP Business Data Cloud offers robust capabilities that enable me to analyze data and extract valuable business insights. It creates a single source of truth with seamless SAP integrations that enable faster, more reliable reporting. It has freed my team from complex engineering efforts by simplifying data analytics, giving us more time to focus on generating insights.
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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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Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
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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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While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
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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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We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
With a S4 backend a lot of core functionality is made simpler - authorization, data types, currency conversion. In particular if the front end choice is SAP Analytics Cloud. The lack of a good connection from Power BI to the datasphere application (instead of the underlying HANA cloud) is a major drawback in that scenario.
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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.
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Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB
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