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While there are many other challengers -- most notably Microsoft's Power -- the choice for buyers of self-service...
business intelligence and analytics tools often still comes down to Tableau vs. Qlik Sense.
So what separates the two data visualization software technologies from one another?
"It's an emphasis on a different perspective," said David Menninger, an analyst at Ventana Research. "Qlik is more suited for building dashboards that show the same information each day. Tableau is more suited to poking around and seeing what's going on."
He added that the two applications are more similar today than they have been in the past. With its earlier QlikView software, Qlik initially emerged more as the vendor of a governed enterprise BI platform built on a strong data processing engine, while Tableau was seen mostly as a tool for ad hoc queries; it usually was sold to business units and departments on the basis of its strong self-service and data visualization capabilities, a so-called land-and-expand strategy that often bypassed IT departments.
But Qlik has invested heavily in its visualization functionality for Qlik Sense, which it released in 2014; doing so has pulled it nearly even with Tableau, Menninger said. Meanwhile, Tableau has introduced a host of enterprise capabilities -- including its data engine, Hyper -- in an effort to make its software more IT-friendly and scalable enough to handle big data applications. Both self-service BI vendors have also been beefing up their data science and advanced analytics capabilities, including machine learning and natural language processing.
"Over the years, they've become more and more similar," Menninger said. "In the grand scheme of things, they are more similar than they are different."
Though the two self-service BI products have had the same general development targets over the last couple of years, that doesn't mean there's no daylight between them. When weighing Tableau vs. Qlik BI and visualization tools, there are still strength and weaknesses to both products.
Pros and cons of Qlik: Functionality, visualization tools
Former Qlik executive Donald Farmer, currently the principal at TreeHive Strategy, said Qlik still has the edge on enterprise functionality. In particular, he said it has strong self-service BI capabilities for setting up repeatable reports, managing data access and scaling to large workloads.
Donald Farmerprincipal, TreeHive Strategy
On the other hand, he said, Tableau has more data connectors, enabling users to connect live to data sources like Teradata and SAP HANA. The software also still has an edge in visualization features, according to Farmer. In addition, customers typically report positive experiences working with the company, which has helped Tableau develop a strong and devoted fan base among its users.
Qlik Sense can also process more data in more ways. The vendor recently made Qlik Sense easier and more cost effective to deploy across a multi-cloud computing environment.
"Qlik has been much more scalable than Tableau, and that's been a strong differentiator," Farmer said. "Tableau's advantage is that people love it. It's well designed."
Pros and cons of Tableau: Hyper and in-memory engine
Over the past few years, Qlik's Associative Engine gave it a clear advantage for higher-end applications. The company built its software around the data engine specifically to help it support enterprise-class BI and data visualization use cases.
But Tableau claims that Hyper, which it added earlier this year, will enable its software to also scale to much larger use cases, including things like IoT analytics and other advanced analytics. Tableau executives have been explicit about how the new data engine is intended to position Tableau for more enterprise adoption -- and put the company on par with Qlik at the engine level as part of the Tableau vs. Qlik Sense battle.
Menninger said it remains to be seen if Hyper will succeed in that regard. The fundamental limiting factor is that it's still an in-memory engine. Hyper does appear to offer substantial performance improvements compared to Tableau's previous engine, he added.
However, he expects data volumes to continue to grow at a fast pace. As a result, what functions as a robust in-memory engine today may come to look sluggish in a couple years.
"I see [Hyper] as extending the life of in-memory technologies to the new world of larger data sets, but I believe it's still an intermediary," Menninger said. "We will continue to see data volumes grow and outpace the Hyper engine."
That isn't necessarily just an issue for Tableau, though. Because much of Qlik's technology is also built around an in-memory data engine, Menninger said the limitation of in-memory technology on big data could eventually bite Qlik and its advanced analytics capabilities as well.
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