Looker is a BI application with an analytics-oriented application server that sits on top of relational data stores. It includes an end-user interface for exploring data, a reusable development paradigm for data discovery, and an API for supporting data in other systems.
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QlikView
Score 8.2 out of 10
N/A
QlikView® is Qlik®’s original BI offering designed primarily for shared business intelligence reports and data visualizations. It offers guided exploration and discovery, collaborative analytics for sharing insight, and agile development and deployment.
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Amazon Redshift
Score 8.9 out of 10
N/A
Amazon Redshift is a hosted data warehouse solution, from Amazon Web Services.
$0.24
per GB per month
Pricing
Looker
QlikView
Amazon Redshift
Editions & Modules
No answers on this topic
QlikView
Custom
per user
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
Offerings
Pricing Offerings
Looker
QlikView
Amazon Redshift
Free Trial
Yes
Yes
No
Free/Freemium Version
No
No
No
Premium Consulting/Integration Services
Yes
Yes
No
Entry-level Setup Fee
Required
Optional
No setup fee
Additional Details
Must contact sales team for pricing.
On an perpetual license basis, based on server plus number of users.
Contact vendor for pricing.
Looker was easier to use, better integration with non-standard datastores, such as Prestodb, and Snowflake, and BigTable. Ease of manageability. Creation of reports faster and easier compared to QlikView. Tableau has better heat maps, however, Looker has better drill down in …
Looker was, hands down, better than any other products we looked at. It was far easier to get started and keep moving because of Looker's internal programming language and data definition language, LookML. We were up and going in just a few days and were creating advanced …
Looker stacks up very well against the other tools we have evaluated and used. All the tools have their own pros and cons. Looker had a better edge in terms of visualizations when we chose to use it. After several updates, other tools began to have newer features. Looker still …
I think working on Looker could be hard, but in performance, it can easily overtake Wave and Zoho Reports. The flexibility of the system and it being super fast makes Looker a standalone from other similar software.
Redshift leapfrogged Hive back when Hive was trying to figure out how to implement indexes, providing a more stable, standardized (postgres), easy to use (any postgres client), easier to administer, and scalable solution for querying server logs and raw usage data.
It's fast processing compared to other products and it's best for structured data analytics & data warehousing purpose. The unique columnar data storage architecture compared to other products makes it the great choice for analytics projects.
Amazon redshift is useful for our data sets due to its low cost and ease of use for the analysts, however, we were considering using BigQuery instead if we had chosen to pursue the Google Analytics 360 product.
When data drives potential for new orders, Looker earns its place in our tech stack. If, on the other hand, we are hoping for pipeline generation, Looker is useful if you are willing to repeatedly go check customer utilizations .... it is not appropriate if you are hoping to automate data analysis for this purpose.
Sales data validations have helped manage our justifications in the past, especially with regard to new product development and new business introduction. It has also been helpful in identifying trends with business impact and direction specific to quarter and monthly sales from ERP data as well as decisions to purchase equipment of staffing based on run rates and product demand.
One thing that can get out of hand is data output - if you aren't careful in your query, you may be overloaded with data dumps and drown in the amount of info you have to filter through. This is a user caution, not a comment on the software itself.
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)
Show visited pages - sessions, pageviews - which programs are viewed the most.
Displays session source/medium views to see where users are coming from.
It shows the video titles, URLs, and event counts so we can monitor the performance of our videos.
It gives a graphic face to the numbers, such as using bar charts, pie graphs, and other charts to show user trends or which channels are driving engagement.
Our clients like to see the top pages visited for a month.
I like the drop-and-drag approach, and building charts is a little easier than it was before.
[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.
We found that QlikView can be a bit slow in supporting some forms of encryption. It is web-based and we needed to upgrade all of our server to not support the older SSL and TLS 1 protocols, only support TLS 1.2 and TLS 1.3. However, QlikView could not run with TLS 1.2 and TLS 1.3. We had to wait over six months to get a version that would handle the newer TLS versions.
There are so many options with QlikView that you can get lost when developing a visualization. There are still items I have not yet figured out, such as labeling a graph with the name of a selected detail item.
QlikView works by pulling the data it is going to use for visualization into its database. I am a security reviewer and I need to make certain that PII and PHI is not pulled by QlikView for a visualization, otherwise this could become a reportable indecent.
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.
I give it this rating because it deems as effective, I am able to complete majority of my tasks using this app. It is very helpful when analyzing the data provided and shown in the app and it's just overall a great app for Operational use, despite the small hiccups it has (live data).
Ease of use, ability to load from pretty much any data source. today I created an application that loaded time sheets from excel that are not in a table format. With Qlik's "enable transformation steps" I was able to automate loads of multiple spreadsheets and multiple tabs easily. Could not do that with any other tool.
Looker is relatively easy to use, even as it is set up. The customers for the front-end only have issues with the initial setup for looker ml creations. Other "looks" are relatively easy to set up, depending on the ETL and the data which is coming into Looker on a regular basis.
QlikView is very easy to implement. The installation is very straight forward. QlikView has several different data connectors that can connect to different data sources very smoothly. The user interface to build the reports is very easy to understand. This helps to have a smaller learning curve. Something very helpful is that QlikView is a browser application for the end users. So, you don't need to install any applications on the user's computer.
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.
Somehow resources heavy, both on server and client. I recommned at least 50Mbs data rate and high performance desktop comouter to be abke to run comolex tasks and configure larger amount of data. On the other hand, the client does not need to worry when viewing, the performance is usually ok
Never had to work with support for issues. Any questions we had, they would respond promptly and clearly. The one-time setup was easy, by reading documentation. If the feature is not supported, they will add a feature request. In this case, LDAP support was requested over OKTA. They are looking into it.
My experience with the Qlik support team has been somewhat limited, but every interaction I have had with them has been very professional and I received a response quickly. Typically if there is a technical issue, our IT team will follow up. My inquiries are specific to product functionality, and Qlik has been very helpful in clarifying any questions I might have.
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
My team attended, but I cannot myself rate, but I think it was good as they've successfully launched a training program at our company themselves for users. It was 3-4 day training.
Training was as expected. The demo environments tend to be more fully featured that our own environment, but the training was clear and well delivered.
"Implementation" can mean a few things... so I'm not sure that this is the answer you want.... but here it goes: To me, implementation means: "Is the user interface intuitive and can I produce meaningful reports with ease?" On that score, I'd say YES. The amount of training required was minimal and the results were powerful. The desktop implementation is a simple, "blank" interface just waiting for your creativity. The pre-populated templates give you a reasonable start to any project -- and a good set of objects to "play around with" if you're just getting started. Finally, note that the "implementation" I used was baked into QuickBooks 2016 Enterprise -- called "Advanced Reporting"..... That integration makes it ultra useful and simple.
Looker Studio, you can easily report on data from various sources without programming. Looker Studio is available at no charge for creators and report viewers. Enterprise customers who upgrade to Looker Studio Pro will receive support and expanded administrative features, including team content management. So it's good.
The only other vendor product that I have worked with that provides a similar experience to Qlikview is Tableau. I would recommend Tableau if your use case is to build a fixed dashboard. You can share reports for free without needing to buy additional licenses. I would recommend Qlikview if your users are looking for a more interactive experience. They can create new objects to represent the data which can't be accomplished as easily in Tableau
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.
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.
Looker has a poignant impact on our business's ROI objectives. As an advertising exchange we have specific goals for daily requests and fill, and having premade Looks to monitor this is an integral piece of our operational capability
To facilitate an efficient monthly billing cycle in our organization, Looker is essential to track estimated revenue and impression delivery by publisher. Without the Looks we have set up, we would spend considerably more time and effort segmenting revenue by vertical.
Looker's unique value proposition is making analytical tools more digestible to people without conventional analytical experience. Other competing tools like Tableau require considerably more training and context to successfully use, and the ability to easily plot different visualizations is one of its greatest selling points.
You can use the free desktop version to do a lot of reporting and analysis work more quickly so the ROI is huge
QlikView is great at finding outliers such as data entry errors
QlikView is great at helping you quickly discover new insights about your business that can prompt you to take action that can immediately affect your cash flow.
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.
