Amazon Redshift is a hosted data warehouse solution, from Amazon Web Services.
$0.24
per GB per month
Tableau Server
Score 7.6 out of 10
N/A
Tableau Server allows Tableau Desktop users to publish dashboards to a central server to be shared across their organizations. The product is designed to facilitate collaboration across the organization. It can be deployed on a server in the data center, or it can be deployed on a public cloud.
$12
Per User Per Month
Pricing
Amazon Redshift
Tableau Server
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
Viewer
$12.00
Per User Per Month
Explorer
$35.00
Per User Per Month
Creator
$70.00
Per User Per Month
Offerings
Pricing Offerings
Amazon Redshift
Tableau Server
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Amazon Redshift
Tableau Server
Considered Both Products
Amazon Redshift
Verified User
Employee
Chose Amazon Redshift
As our applications are hosted on AWS service, Redshift is the best option for us. Also, it provide a near to real-time performance on limited datasets and less complex queries. High availability is the major concern for any growing business and AWS is the best option for this. …
Most of our stack is on AWS, so while Snowflake and BigQuery was a viable option from a performance perspective, it was easier to integrate with RedShift. We considered hosting SQL Server on AWS or using Amazon RDS (Postgres or MySQL), however, the self-service aspect of …
QlikView can't connect to live data (in general) Licensing Costs of QlikView and Cognos are expensive. Cognos doesn't have excellent Graphics embedded within the tool
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)
Whole funnel and specific channel performance from upper to lower funnel metrics. The ability to view full channel performance for some time, such as weekly, monthly, or quarterly, has truly been monumental in how my team optimizes specific channels and campaigns. Daily performance tracking is a bit overwhelming, with load times and having to refresh specific live views over time. It can be challenging to do so at times, as extensive dashboards take much longer to load.
[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.
It's good at doing what it is designed for: accessing visualizations without having to download and open a workbook in Tableau Desktop. The latter would be a very inefficient method for sharing our metrics, so I am glad that we have Tableau Server to serve this function.
Publishing to Tableau Server is quick and easy. Just a few clicks from Tableau Desktop and a few seconds of publishing through an average speed network, and the new visualizations are live!
Seeing details on who has viewed the visualization and when. This is something particularly useful to me for trying to drive adoption of some new pages, so I really appreciate the granularity provided in Tableau Server
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.
Tableau Server has had some issue handling some of our larger data sets. Our extract refreshes fail intermittently with no obvious error that we can fix
Tableau Server has been hard to work with before they launched their new Rest API, which is also a little tricky to work with
It simply is used all the time by more and more people. Migrating to something else would involve lots of work and lots of training. The renewal fee being fair, it simply isn't worth migrating to a different tool for now.
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.
Tableau Server takes training and experience in order to unlock the application's full potential. This is best handled by a qualified data scientist or data analytics manager. Tableau user interface layout, nomenclature, and command structure take time and training to become proficient with. Integration and connectivity require proper IT developer support.
Our instance of Tableau Server was hosted on premises (I believe all instances are) so if there were any outages it was normally due to scheduled maintenance on our end. If the Tableau server ever went down, a quick restart solved most issues
While there are definitely cases where a user can do things that will make a particular worksheet or dashboard run slowly, overall the performance is extremely fast. The user experience of exploratory analysis particularly shines, there's nothing out there with the polish of Tableau.
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
We have consistently had highly satisfactory results every time we've reached out for help. Our contractor, used for Tableau server maintenance and dashboard development is very technically skilled. When he hits a roadblock on how to do something with Tableau, the support staff have provided timely and useful guidance. He frequently compares it to Cognos and says that while Cognos has capabilities Tableau doesn't, the bottom line value for us is a no-brainer
In our case, they hired a private third party consultant to train our dept. It was extremely boring and felt like it dragged on. Everything I learned was self taught so I was not really paying attention. But I do think that you can easily spend a week on the tool and go over every nook and cranny. We only had the consultant in for a day or two.
The Tableau website is full of videos that you can follow at your own pace. As a very small company with a Tableau install, access to these free resources was incredibly useful to allowing me to implement Tableau to its potential in a reasonable and proportionate manner.
Implementation was over the phone with the vendor, and did not go particularly well. Again, think this was our fault as our integration and IT oversight was poor, and we made errors. Would they have happened had a vendor been onsite? Not sure, probably not, but we probably wouldn't have paid for that either
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.
Today, if my shop is largely Microsoft-centric, I would be hard pressed to choose a product other than Power BI. Tableau was the visualization leader for years, but Microsoft has caught up with them in many areas, and surpassed them in some. Its ability to source, transform, and model data is superior to Tableau. Tableau still has the lead in some visualizations, but Power BI's rise is evidenced by its ever-increasing position in the leadership section of the Gartner Magic Quadrant.
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.
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.
Tableau does take dedicated FTE to create and analyze the data. It's too complex (and powerful) a product not to have someone dedicated to developing with it.
There are some significant setup for the server product.
Once sever setup is complete, it's largely "fire and forget" until an update is necessary. The server update process is cumbersome.
