MySQL vs. Quixy vs. SAP HANA Cloud

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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Quixy BPM for managing business processes distinguishes itself through its user-friendly interface and the absence of any coding requirements. This makes it an ideal solution for companies looking to streamline their operations. Quixy BPM is suitable for businesses of all sizes and represents a cost-effective way to save time and effort.

I think if you have a large organization, it's probably the product and the marketplace to go to. We're a large management consulting firm operating in four to seven countries. And generally speaking, I think that's the size and the scope where it scales best. I can't speak to smaller companies, but I can't see smaller companies leveraging the benefits as much as a larger organization can.

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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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• Forms Automation: Quixy helps us in developing forms within minutes and hours with simple drag and drop.
• Report Builder: The report builder tool allows you to generate customized reports based on the data collected available in various data sources.
• Integration: Integration with external systems through API's.

• Real-time reporting and analytics on data: because of its in-memory architecture, it is perfect for businesses that need to make quick decisions based on current information.
• Managing workload with complex data: it can handle a vast range of data types, including relational, documental, geospatial, graph, vector, and time series data.
• Developing and deploying intelligent data applications: it provides various tools for such applications and can be used for machine learning and artificial intelligence to automate tasks, gain insights from data, and make predictions.

• 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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• Better UI/UX will take the platform to next level.
• Application Library: Having base versions of frequently used applications in the app library helps the users to build applications quickly.
• Having more online help content will help the users to resolve the issues on their own.

• Requires higher processing power, otherwise it won't fly. How ever computing costs are lower. Incase you are migrating to cloud please do not select the highest config available in that series . Upgrading it later against a reserved instance can cost you dearly with a series change
• Lack of clarity on licensing is one major challenge
• Unless S/4 with additional features are enabled mere migration HANA DB is not a rewarding journey. Power is in S/4

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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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We would rate our likelihood of renewing at 9/10. SAP HANA Cloud has proven to be a highly reliable and scalable data platform that consistently delivers strong performance. Its seamless integration with our overall SAP landscape, combined with improved analytics and real-time data capabilities, makes it a core part of our long-term technology strategy.

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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.

Quixy has allowed us to focus on more important tasks, as the platform takes care of labor-intensive administrative work. The automation of various processes has been invaluable, as it has saved us a considerable amount of time and resources. Overall, Quixy has transformed our administrative work and has enabled us to allocate more resources to critical tasks, leading to better outcomes for our organization.

It is very useful solution which provides you speedier data processing, real-time analytics. It helps you manage diverse data types. It also offers you excellent disaster management. It has user friendly interface which helps you navigate system and transactions easily and perform task smoothly.

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so far, we didn't get any outage

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so far good

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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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However, I am not the right person to answer this as we have another department to handle support and contact the service provider for any support required. Although i will say that they are the quick respondent and knows how to handle querry of the customers and provide quick and better support.

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

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Professional GIS people are some of the most risk-averse there are, and it's difficult to get them to move to HANA in one step. Start with small projects building to 80% use of HANA spatial over time.

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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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While Excel is a powerful tool for organizing data and creating basic inventory spreadsheets, it lacks the automation and integration capabilities that Quixy provides. Also, we can integrate with other business systems, such as accounting and order fulfillment systems. So, we can actually have centralized system connected across several departments for automation.

I have deep knowledge of other disk based DBMSs. They are venerable technology, but the attempts to extend them to current architectures belie the fact they are built on 40 year old technology. There are some good columnar in-memory databases but they lack the completeness of capability present in the HANA platform.

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I don't have visibility in licensing

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Limitation of training deliverable by organization

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We are still in process for the first applciaiton

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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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• Faster Digitalization (time is money)
• Step by Step and independent transition for every department
• Automation of 70% of our manual process till date and counting

• ROI has always been high in terms of the functionality that it offers and the security features it comes with.
• Managing large volumes of data in real-time is not an easy task, but it does it pretty well with faster data processing.

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