Amazon Redshift vs. SAP HANA Cloud

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)

Incentivized

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.

Incentivized

• 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.

Incentivized

• SAP HANA Cloud can help drive data analytics, data migration, and data management exceptionally well.
• It offers an integration service that lets you integrate data and processes with 3rd party app or any other cloud app.
• In-memory capability helps in faster data processing.

Incentivized

• 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.

Incentivized

• 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

Incentivized

At this moment we are not focusing on SAP, however would love to in the future. This is primarily because of our limited ability to generate more revenue to fund for SAP partnerships and products. Our initial tryst with SAP Partneredge open ecosystem didn't go as planned and we have shelved that for now. Hope we can revive in the future

Incentivized

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.

Incentivized

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.

Incentivized

so far, we didn't get any outage

Incentivized

so far good

Incentivized

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

Incentivized

One specific example of how the support for SAP HANA Cloud impacted us is in our efforts to troubleshoot and resolve technical issues. Whenever we encountered an issue or had a question, the support team was quick to respond and provided us with clear and actionable guidance. This helped us avoid downtime and keep our analytics operations running smoothly.

Incentivized

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.

Incentivized

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[.]

Incentivized

It enables preview and better cloud service than other cloud platforms. Easy document transfer and faster document transfer are the key points for the selection of the HANA cloud server. The preview of data before its execution is also one of the factors in the selection of the HANA server.

Incentivized

Limitation of training deliverable by organization

Incentivized

• It allows for an almost seamless integration of our data which can then be used by other departments for analytical purposes.
• No in house resources are needed for keeping the data alive and performing backup/migration tasks of the data in its end state.

Incentivized

• Enhanced agility and innovation, improved decision-making, and reduced IT infrastructure costs are some positive impacts.
• The process of migrating data and applications to the cloud may require downtime and disrupt operations.
• It involves implementing additional security controls and addressing data residency requirements, which can have a negative impact.