Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
When it comes to big data processing, I prefer Databricks over other solutions.
For a lot of different tasks, including machine learning, it is a nice solution.
In my organization, we moved from OBI to Qlik Sense due to limitations with OBI, resulting in very high ROI.
Whenever we reach out, they respond promptly.
While tech support is comprehensive, the stability of Qlik Sense means I generally do not need it.
In Turkey, the consultant firms are very professional, and they support you.
I think they lack in the support system.
The patches have sometimes caused issues leading to our jobs being paused for about six hours.
It performs well in terms of performance and load compared to others.
It is extensible.
They release patches that sometimes break our code.
Cluster failure is one of the biggest weaknesses I notice in our Databricks.
The stability is very good.
It would be beneficial to have utilities where code snippets are readily available.
Adjusting features like worker nodes and node utilization during cluster creation could mitigate these failures.
We prefer using a small to mid-sized cluster for many jobs to keep costs low, but this sometimes doesn't support our operations properly.
Power BI has better visualizations and interactions with updates in 2023 that provide ease of use.
Providing an API feature to access data from the dashboard or QEDs could be beneficial.
Maybe more AI or real-time analytics could be incorporated.
For small or large organizations needing many or few licenses, pricing varies.
Compared to Power BI, it is definitely costly.
Among the BI tools and data analytics tools, Qlik is the most expensive.
Databricks' capability to process data in parallel enhances data processing speed.
The notebooks and the ability to share them with collaborators are valuable, as multiple developers can use a single cluster.
From an end-user perspective, it's convenient and performance-oriented, providing something meaningful from all the organization's data.
It is a single product that I can use as an ETL database, BI, and more.
It has an interactive interface with Qlik graphs, pivot, and interactivity, which makes it easier to use than other tools.
Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.
Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.
What are the key features of Databricks?
What are the benefits or ROI to look for in Databricks reviews?
Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.
Qlik Sense is a visual analytics and business intelligence (BI) platform that gives users full control over their system’s data. From this platform they can control every aspect of their system data. It maximizes an organization’s ability to make decisions driven by their data.
Benefits of Qlik Sense
Some of the benefits of using Qlik Sense include:
Reviews from Real Users
Qlik Sense stands out among its competitors for a number of reasons. Two major ones are its associative analytics technology and its remote access capability. Qlik Sense employs an associative analytics engine that gives users the ability to take their data analytics to the next level. Users can create visual connections between different datasets spread across their network, creating deep insights that enable users to gain a full understanding of their data. This engine is easily scaled up to allow a large number of users to benefit from the deep insights that it provides. Users can access Qlik Sense from anywhere in the world. Qlik Sense has an online portal that can be used consistently from anywhere at all. Having the ability to remotely analyze data gives users flexibility when it comes to choosing how to deploy their manpower.
Jarno L., the managing director of B2IT, writes, “The associative technology features are the solution's most valuable aspects. Qlik was the first company to implement an in-memory associative analytics engine. This basically means that all data is loaded into memory, but it also means that instead of joining data together, the data is associated together. From the front end, from the user interface point of view, data can be joined or included or excluded on the fly. It can be drilled down and drilled through and users can slice and dice it and that type of thing can be done from anywhere in the data to any other place in the data. It doesn't have to be predefined. It doesn't have to have hierarchies or anything like that.”
Tami S., the senior business intelligence analyst at the La Jolla Group, writes, “With the changing business landscape, it is nice to access Qlik Sense through an external website. As an organization when we use QlikView Desktop, we need to connect to our internal network. We can access QlikView through the QlikView access point but the website has a little different look and feel than the desktop application. We appreciate that Qlik Sense is browser-based and the user experience is the same whether at home, in the office or on a boat. As long as the user has internet access, performance is the same.”
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