Amazon Redshift is a hosted data warehouse solution, from Amazon Web Services.
$0.24
per GB per month
SAP Datasphere
Score 8.3 out of 10
N/A
SAP Datasphere, the next generation of SAP Data Warehouse Cloud, is a comprehensive data service that enables data professionals to deliver seamless and scalable access to mission-critical business data. It provides a unified experience for data integration, data cataloging, semantic modeling, data warehousing, data federation, and data virtualization. SAP Datasphere enables users to distribute mission-critical business data — with business context and logic preserved — across the data…
N/A
Pricing
Amazon Redshift
SAP Datasphere
Editions & Modules
Redshift Managed Storage
$0.24
per GB per month
Current Generation
$0.25 - $13.04
per hour
Previous Generation
$0.25 - $4.08
per hour
Redshift Spectrum
$5.00
per terabyte of data scanned
No answers on this topic
Offerings
Pricing Offerings
Amazon Redshift
SAP Datasphere
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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SAP Datasphere is available as a subscription or consumption-based model. The SAP Datasphere capacity unit (CU) offers an adaptable approach to pricing that enables any workload on any hyperscaler. The number of CUs required is determined by the unique workload, with the ability to tailor the combination of required services within SAP Datasphere utilizing a flexible tenant configuration. The services that contribute to CU consumption are the core application (compute and storage), data lake, BW bridge, data integration, and data catalog (crawling and storage).
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)
SAP is best suited for large global corporations. It is a very complex software and is difficult to come by individuals who have sufficient enough knowledge to master the product. Globally our company only has 1 person to support us in IT for SAP. It is great if you use a more complex web host such as SFCC as you can make connections to SAP for returns, inventory, price updates, etc.
Redshift is fully managed. Small teams do not have the resources to maintain a cluster. CloudWatch metrics are provided out-of-the-box, and it is easy to configure alarms.
Redshift's console allows you to easily inspect and manage queries, and manage the performance of the cluster.
Redshift is ubiquitous; many products (e.g., ETL services) integrate with it out-of-the-box.
Writing .csvs to S3 and querying them through Redshift Spectrum is convenient.
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.
It could benefit from adding data integrity and programming tools common to other database management systems.
Amazon Redshift is based on PostgreSQL 8.0.2. That version of PostgreSQL was released in December 2006. While PostgreSQL was much improved since then, the new features were not implemented in Redshift. Many basic features are missing from it.
Primary keys can be declared but not enforced. Referential integrity (foreign keys) can be declared but not enforced. UNIQUE and CHECK constraints are not supported and cannot be declared.
IDENTITY can be declared on a column, and Redshift will put unique values into it. However: IDENTITY values in the newly inserted rows won’t be incremental or sequential. To implement a sequential number, you need to write your own custom code.
There are no stored procedures in Redshift. We are writing SQL script files, and then parsing and running them one statement at a time from a Python program. This also enabled us to implement execution-time error logging.
In SQL scripts, to check for the row count of affected rows, a complicated join query against some system tables or views has to be executed.
Data Control Language (DCL) does not exist. No statements like IF, WHILE, DO, RAISERROR, etc.
On performance of views… Views do not “pass-through” a query parameter which is a potential problem for performance.
When selecting against a view with the WHERE clause outside of the view, the inner query of the view will be executed first without consideration for the WHERE clause, and only then the WHERE clause will be applied.
Certain clauses of SQL work many times faster than other clauses. So be careful and test your statements for performance earlier rather than later, especially if working with a large data set.
There was a situation when DELETE FROM JOIN was unacceptably slow. Replacing JOIN with the USING clause made DELETE instantaneous.
Overall it serves all our aspects of data management like data cleaning, data manipulation, and data reporting on the cloud platform. We can create stored procedures and triggers in it very easily as all the options are self suggested in it. We can easily attach the results of ARS to the other tools as well for drawing the statistical results.
It is one of the best tools and a boon to Logistics teams across the globe. One tends to actually process warehousing data so smoothly and the way demonstration is made while in programs it makes it user friendly. The Inventory touch points that one identify is simply awesome and is best part.
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
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.
We evaluated [Amazon] Redshift vs BigQuery vs Amazon EMR, back in 2014. Back then BigQuery cost was slightly higher than that of [Amazon] Redshift price structure. Amazon EMR, needs lots more management (Admin tasks) and EMR is designed to be ephemeral and not designed to be a data store. [Amazon] Redshift was ideal with the price structure, performance and ROI[.]
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.
