Amazon Redshift vs. SAP Datasphere

If the number of connections is expected to be low, but the amounts of data are large or projected to grow it is a good solutions especially if there is previous exposure to PostgreSQL. Speaking of Postgres, Redshift is based on several versions old releases of PostgreSQL so the developers would not be able to take advantage of some of the newer SQL language features. The queries need some fine-tuning still, indexing is not provided, but playing with sorting keys becomes necessary. Lastly, there is no notion of the Primary Key in Redshift so the business must be prepared to explain why duplication occurred (must be vigilant for)

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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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• [Amazon] Redshift has Distribution Keys. If you correctly define them on your tables, it improves Query performance. For instance, we can define Mapping/Meta-data tables with Distribution-All Key, so that it gets replicated across all the nodes, for fast joins and fast query results.
• [Amazon] Redshift has Sort Keys. If you correctly define them on your tables along with above Distribution Keys, it further improves your Query performance. It also has Composite Sort Keys and Interleaved Sort Keys, to support various use cases
• [Amazon] Redshift is forked out of PostgreSQL DB, and then AWS added "MPP" (Massively Parallel Processing) and "Column Oriented" concepts to it, to make it a powerful data store.
• [Amazon] Redshift has "Analyze" operation that could be performed on tables, which will update the stats of the table in leader node. This is sort of a ledger about which data is stored in which node and which partition with in a node. Up to date stats improves Query performance.

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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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• We've experienced some problems with hanging queries on Redshift Spectrum/external tables. We've had to roll back to and old version of Redshift while we wait for AWS to provide a patch.
• Redshift's dialect is most similar to that of PostgreSQL 8. It lacks many modern features and data types.
• Constraints are not enforced. We must rely on other means to verify the integrity of transformed tables.

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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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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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Just very happy with the product, it fits our needs perfectly. Amazon pioneered the cloud and we have had a positive experience using RedShift. Really cool to be able to see your data housed and to be able to query and perform administrative tasks with ease.

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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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The support was great and helped us in a timely fashion. We did use a lot of online forums as well, but the official documentation was an ongoing one, and it did take more time for us to look through it. We would have probably chosen a competitor product had it not been for the great support

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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.

Than Vertica: Redshift is cheaper and AWS integrated (which was a plus because the whole company was on AWS).
Than BigQuery: Redshift has a standard SQL interface, though recently I heard good things about BigQuery and would try it out again.
Than Hive: Hive is great if you are in the PB+ range, but latencies tend to be much slower than Redshift and it is not suited for ad-hoc applications.

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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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Redshift is relatively cheaper tool but since the pricing is dynamic, there is always a risk of exceeding the cost. Since most of our team is using it as self serve and there is no continuous tracking by a dedicated team, it really needs time & effort on analyst's side to know how much it is going to cost.

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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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• Our company is moving to the AWS infrastructure, and in this context moving the warehouse environments to Redshift sounds logical regardless of the cost.
• Development organizations have to operate in the Dev/Ops mode where they build and support their apps at the same time.
• Hard to estimate the overall ROI of moving to Redshift from my position. However, running Redshift seems to be inexpensive compared to all the licensing and hardware costs we had on our RDBMS platform before Redshift.

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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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