Amazon Redshift vs. Supermetrics

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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If you are looking to pull and aggregate data from multiple sources for reporting or analytics, Supermetrics is the best option for connecting those data sources into a single table. Supermetrics is less beneficial if you report on a single data source or do not need to aggregate your data into a single source.

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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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• Supermetrics is easy to use, the ui is helpful for creating queries.
• Supermetrics allows to run the created queries on triggers.
• Supermetrics allows to connect with different data sources like Google analytics etc .,
• Supermetrics sends alert on the failure of queries to the desired email address

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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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• Sometimes I have to refer to the website to find which metrics are what - the names aren't always the same as the platform calls them.
• No public data for LinkedIn.
• Definitely requires knowledge on how to use Google Data Studio.

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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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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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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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Supermetrics is better because of its ease of use and it mirrors most of the metrics on ad platforms. For some similar reporting platforms, metrics are often called something slightly different or are not able to pull the same data as presented on the ad platform; Supermetrics is the closest you'll get to exact data alignment.

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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! Supermetrics helped us transition into Google Data Studio as our monthly reporting system.
• Savings! We saved money by switching our reporting to Google Data Studio + Supermetrics.
• Time! We save a lot of time on our monthly reports thanks to Supermetrics.

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