Amazon Redshift vs. SAP Adaptive Server Enterprise (ASE)

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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We use this for an inbuilt security management system, where it performs well in a scaled setup with a large volume of live data with high availability. Also, the performance is up to the mark for the large statement flow. From a DBA perspective, a lot of parameters need to be fine-tuned for the specific environment needs, which can cause overhead. Expertise is limited, and the learning curve is steep for the SAP ASE.

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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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• High availability and reliability.
• High performance.
• Monitoring of threshold based events.
• Security at multiple levels.
• Query plan optimization.
• Lock management.
• Access to HANA.

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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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• A quick button for devs to switch instances into a dev mode (eliminating logs, and such).
• Licensing is far too complicated. Simplify pricing.

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Our licenses are perpetual. It is the support that we will be renewing. We will renew because we continue to use and receive value from the product.

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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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Well-suited in the security domain, high performance, and low latency of the DBMS. In terms of the DBA perspective, a dedicated monitoring tool (Cockpit) helps a lot in terms of managing the database, which helps in identifying bottlenecks during performance issues. Also, it helps us to send custom alerts related to Database activities.

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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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Incredibly responsive, saving us countless hours in troubleshooting.

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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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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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• 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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• Positive ROI.
• Ease of use with minimal training required to write high performance SQL (assumes a knowledge of SQL already).
• Ease of database administration.
• Sometimes upgrades can be difficult.
• Changing platforms can be difficult (changing say from SPARC to Intel).
• Changing operating systems can be difficult (changing from Solaris to linux).

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