Open source proponents are quick to list the benefits of this type of software, with lower purchase costs being a primary reason for most organizations' interest in using it instead of proprietary commercial systems.
Other benefits open source proponents often cite include the ability to innovate on and customize the code based on enterprise needs.
Organizations that use open source to build their data management capabilities often do see such benefits, experts said.
On the other hand, however, many enterprise IT leaders also encounter significant challenges. Those challenges and resulting missteps can blunt the success of -- or even totally derail -- their data management initiatives.
Here, several experts shared five common problems they see IT face when using open source data management software:
1. Underestimating the required resources
Technology teams often underestimate the amount of time and skill needed to successfully use open source software when building out their data management environment, said William McKnight, president of McKnight Consulting Group.
"There's generally an underestimation of the work required," he said. "They think it's in the cloud and they won't have to do much, but they have to bring a lot of expertise to bear."
Open source requires teams to have the right mix of programming, architecture and database administration skills, along with cloud computing knowledge and security acumen. They also must understand the business objectives for the initiative to deliver a system of value.
Moreover, those teams need to manage, maintain, upgrade and innovate the code throughout its life, so there's an ongoing need for fairly intensive resources, McKnight said.
"You have to trigger a lot of management activities, but there's a payoff: If you do the work well, open source has a great chance of success that can deliver great value," he said.
2. Glossing over the absence of vendor support
Many enterprise IT teams rely on vendor support to supplement their in-house skills. That support isn't there with open source and it's a reality some teams fail to fully appreciate.
"The inability to call technical support, the lack of a support community is hard. You have to navigate issues alone," said Brad Ptasienski, a partner at digital consulting firm West Monroe and its data engineering and analytics market lead.
Of course, organizations can -- and do -- turn to open source communities for collaboration and support, but it's not the same as having contractually mandated service-level agreements with a commercial software supplier. IT must plan for that.
"There are plenty of open source communities that are really robust, but I'm not saying I'd want my clients relying on them for mission-critical things," McKnight said.
3. Creating silos
"Some of these open source tools are so independent of the other tools that they don't provide [needed] uniformity and they don't connect and integrate easily," said Noel Yuhanna, vice president and principal analyst at Forrester Research.
He added, "They work in silos, they don't interoperate with other tools, and that makes it harder for them to provide benefits to the business."
This can be especially problematic for data programs, as enterprises have data coming from multiple systems.
As a result, technology teams should be prepared to spend more time and effort on bringing together and integrating open source products than they'd spend doing such work if they had used proprietary software, Yuhanna said.
4. Miscalculating the total cost of ownership
According to Yuhanna, organizations frequently miscalculate the total cost of ownership of their open source systems because they underestimate the amount of integration work required with open source and the lack of external support as well as the time and skills open source software needs throughout its lifecycle.
"They get attracted to the low Capex, but the Opex is what hits them," he said.
5. Mismanaging when scaled
Many organizations work through pilot open source projects without big challenges, but they encounter many issues when they then try to manage those deployments at scale.
In such cases, they don't have the level of integration required for the systems to work effectively, they don't have the needed agility and automation to keep pace or they don't have the appropriate governance and controls in place to secure them.
For example, Sanjay Srivastava, chief digital officer at business transformation services firm Genpact, said he sees architecture and development teams struggle to track the changes in the open source code they're using. This could create security exposures and other problems in the systems' operations.
He also sees teams implementing fixes or innovations, but they fail to track them and build a strategy to manage such updates holistically. That leads to overlaps and redundancies in the code which can cause a drag on performance and interoperability.
To succeed with open source at scale, IT managers must dedicate resources to managing it.
"It's not a side task," Srivastava said. "It's a main job."