Google Cloud SQL vs. MySQL vs. SAP Datasphere

Does what it promises well, for instance, as a sidecar for the main enterprise data warehouse. However, I would not recommend using it as the main data warehouse, particularly due to the heavy business logic, as other dedicated tools are more suitable for ensuring scalable operations in terms of change management and multi-developer adjustments.

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MySQL is best suited for applications on platform like high-traffic content-driven websites, small-scale web apps, data warehouses which regards light analytical workloads. However its less suited for areas like enterprise data warehouse, OLAP cubes, large-scale reporting, applications requiring flexible or semi-structured data like event logging systems, product configurations, dynamic forms.

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SAP Datasphere is well suited for scalable cloud based data integration scenarios which also opens up the doors for AI driven insights which are much harder to achieve with on-prem data warehouses. Considering the licensing model of SAP Datasphere being based on consumption driven capacity units cost can be a big consideration for organizations with large volumes of data that can be a pre-requisite for data mining and AI use cases. So this can be a bottleneck or not so well adopted scenario for SAP Datasphere.

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• It has a easily and user understandable interface which provides it every necessary feature to come up with.
• It's backend is very strong that can help us to run big quieres without any hesitation.
• It's integration with other tools are one of the powerful feature which makes it more suitable to use.

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• Stable - it just runs, with minimal downtime or errors
• Fast - well-structured data is quickly written and read
• Secure - MySQL is easy to keep data secure from people and applications that shouldn't see it
• Easy to use - SQL is industry standard so no problems with adding, editing and reading data stored in MySQL

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• SAP Data Warehouse Cloud offers free trial for 90 days with free 128 GB of storage and 64 GB memory.
• Availability of self-service data modeling and analytics on SAP Data Warehouse Cloud enables users to access and analyze data without getting support from the IT team.
• Without zero coding while collecting, connecting, analyzing and modeling data, it saves us time and operational costs of partnering with external IT support experts.

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• Increasing support for more database engines may enable a wider range of application needs to be met.
• Implementing and updating cutting-edge security features on a constant basis.
• Streamlining and enhancing the tools for transferring data to Google Cloud SQL from on-premises databases or other cloud providers.

• Learning curve: is big. Newbies will face problems in understanding the platform initially. However, with plenty of online resources, one can easily find solutions to problems and learn on the go.
• Backup and restore: MySQL is not very seamless. Although the data is never ruptured or missed, the process involved is not very much user-friendly. Maybe, a new command-line interface for only the backup-restore functionality shall be set up again to make this very important step much easier to perform and maintain.

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• Need to have a good understanding of the SAP ecosystem to implement and use it.
• From a cost perspective it can be little bit on the expensive side for enterprises.
• The platform is still new and hence more subjected to bugs. But support for it is always good from the SAP team.

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It fits the current needs and bandwith of out lean organization.

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For teaching Databases and SQL, I would definitely continue to use MySQL. It provides a good, solid foundation to learn about databases. Also to learn about the SQL language and how it works with the creation, insertion, deletion, updating, and manipulation of data, tables, and databases. This SQL language is a foundation and can be used to learn many other database related concepts.

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Datasphere can come with its own challenges which can feel like a mountain to get over. However, once one has an understanding of how the product works it becomes easier to use. Once the time is spent to get it setup and working correctly very little is needed to keep it running smoothly. Its a great tool it just takes time to learn.

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As with other cloud tools, users must learn a new terminology to navigate the various tools and configurations, and understand Google Cloud's configuration structure to perform even the most basic operations. So the learning curve is quite steep, but after a few months, it gets easier to maintain.

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I give MySQL a 9/10 overall because I really like it but I feel like there are a lot of tech people who would hate it if I gave it a 10/10. I've never had any problems with it or reached any of its limitations but I know a few people who have so I can't give it a 10/10 based on those complaints.

SAP has suggested that BW 7.5 will be sunset soon. Usability is good in SAP BW Modernization. Instead of going with other non-SAP tools, staying with SAP will be suitable for existing users. Across the board, many of them are moving to DataSphere.

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GCP support in general requires a support agreement. For small organizations like us, this is not affordable or reasonable. It would help if Google had a support mechanism for smaller organizations. It was a steep learning curve for us because this was our first entry into the cloud database world. Better documentation also would have helped.

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We have never contacted MySQL enterprise support team for any issues related to MySQL. This is because we have been using primarily the MySQL Server community edition and have been using the MySQL support forums for any questions and practical guidance that we needed before and during the technical implementations. Overall, the support community has been very helpful and allowed us to make the most out of the community edition.

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I would greatly acknowledge the services of Sap Data [warehouse Cloud] because we were struggling before its arrival where we used to get manual data connections and this used to consume a lot of time but after its use, we now are able to connect data easily saving a lot of time and finances.

1. Estimate your data size. 2. Test, test, and test.

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Unlike other products, Google Cloud SQL has very flexible features that allow it to be selected for a free trial account so that the product can be analyzed and tested before purchasing it. Integration capabilities with most of the web services tools are easier regarding Google Cloud SQL with its nature and support.

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MongoDB has a dynamic schema for how data is stored in 'documents' whereas MySQL is more structured with tables, columns, and rows. MongoDB was built for high availability whereas MySQL can be a challenge when it comes to replication of the data and making everything redundant in the event of a DR or outage.

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Each of these listed software has its own unique strength and capacity that scales well. SAP Datasphere on its end up against them with more suitability for large establishments with complex data ecosystems with scalability support. Also, it avails a pay-as-you-go pricing for users, and it is widely up for data quality, data governance, and data discovery.

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Despite the pricing model being expensive for small businesses, it provides decent features and capabilities for organizations of different sizes and it's an appropriate investment in today's business environment where there is constant pressure to build a scalable and flexible analytics service

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Ever since we implemented SAP Data Warehouse Cloud, we have been able to reduce the additional costs of hiring third-party service providers by incorporating professional services offered by the vendor.

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• Improved integration with Google Cloud, we have set up some automations with Google Workspace, and we have noticed that the raw data sharing between them is very fast as compared to using some other managed database, not sure why.
• Due to some downtime during maintenance, we had to set up a relatively small service which ingested the data while this went down and dumped it when it came back up. So this was a negative impact on our ROI, since now we had to remedy this downtime against the same profit margins
• It was cheaper than the legacy aws service since we needed large database instances

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• As it is an open source solution through community solution, we can use it in a multitude of projects without cost license
• The acquisition by Oracle makes you need to contract support for the enterprise version
• If you have knowledge about oracle databases, you can get more out of the enterprise version

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• Preserving data quality has enhanced governance on data by having a single source that is accessible to every business user via self-service capabilities.
• Operational cost is lowered by connecting data in one integrated solution hence making it easy to access information without having to keeping logging to other applications. Additionally, no external IT support is needed since SAP Data Warehouse Cloud has no-coding modeling tools.
• SAP Data Warehouse Cloud has enabled every business user to understand different data by transforming data to real insights.

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