Amazon Redshift vs. SnapLogic

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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Snaplogic is unique from other IPASS tools if you're very sensitive about data security as they have an on-premise option where your data never needs to leave your data center. And data pipelines can be quickly created if Snaplogic has the requisite connector to your data sources. On the downside, if you're transforming a large amount of data for example in training machine learning models, a tool with elastic compute capability is more appropriate.

• [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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• Easy access to any type of source system. Data could be in any format.
• Very beautiful visual representation of transforms that makes it super easy to use it by any non developer.
• It can be run in cloud or on-premise. helping you choose your comfort of security.
• Has pretty good customer support and have recently started their community forum as well.

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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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• They need to have a way to connect to GitHub to allow the users to maintain their version control in GitHub. This is a missing functionality.
• As pipelines become complex, it's difficult to have all the snaps stitched together - just like to see it done differently.
• They do not have a way to start/stop a preview. This is hard to use, especially if you have to stop an accidental preview invocation.

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This has been hands down the BEST software company I have ever used and dealt with. I am a 25 year IT veteran at this college. They go above and beyond in soliciting our feedback/input and proactively follow up about bugs, issues, etc. I have given multiple potential clients my thoughts and after seeing the SL demo they all sign up. I appreciate their support model, it's REFRESHING!

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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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It is very powerful but has a steep learning curve

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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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They can be prompt but they have not been as useful as I've wanted. We had a bug that affected many of our customers through an API connection between SnapLogic and our platform. Eventually they were able to figure it out, but it took a long time of negotiating between our engineering team and theirs. Additionally, we installed the SnapLogic groundplex for our customers and we've run into a bunch of problems of connectivity. If SnapLogic offered to be on those calls with our clients to troubleshoot how to fix these problems, I would give them a better grade here.

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The groundplex in our VPC is very nice for security reasons and the SnapLogic team was extremely helpful during our implementation

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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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We opted for SnapLogic due its ease of use and the flexibility it offers, it was the platform that was strongest in both application integration and data integration and both were use cases we wanted to be able to cover.

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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• We have cut development time down by at least 70%
• The software was more on the expensive side at renewal which required some further approvals to be sought for the spend
• More developers are able to build and use Snaplogic pipelines in their projects

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