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| Source: Gartner. The Hype Cycle for Data Management, 2017. |
"Data management continues to be central to the move toward digital business. As requirements change within the architecture of the organisation and place greater demands on underlying technology, the maturity and capability of many of the technologies highlighted in the Hype Cycle will advance rapidly," said Donald Feinberg, VP and Distinguished Analyst at Gartner. "Recent years have seen many new additions to the Hype Cycle, including in-memory, cloud, data virtualisation, advanced analytics, data as a service, machine learning, graph, non-relational and Hadoop."
Graph database management systems (DBMSes) represent data in graph structures such as nodes and edges, while non-relational data structures can include graph DBMSes as well as document store DBMSes, which store data in individual documents; Hadoop; SQL interfaces; key-value DBMSes, which store data in associative arrays; and wide-column DBMSes, which store data in columns.
Two technologies are of particular interest as they show the impact cloud computing is having on the data management discipline, Gartner said. Hadoop distributions are deemed to be obsolete before reaching the Plateau of Productivity because the complexity and questionable usefulness of the entire Hadoop stack is causing many organisations to reconsider its role in their information infrastructure. Instead, organisations are looking at increasingly competitive and convenient cloud-based options with on-demand pricing and fit-for-purpose data processing options.
As part of the same cloud-led trend, SQL interfaces to cloud object stores have appeared at the Innovation Trigger stage. "We expect these interfaces to represent the future of cloud database platform as a service (PaaS) and reach the Plateau within two to five years because they are the focus of most cloud vendors and products in this space," said Feinberg. "They enable organisations to interact with data stored in the cloud, using a familiar SQL syntax. Object stores are well suited to storing large volumes of multistructured data, typical of data lakes."
Of the 35 other technologies highlighted on the 2017 Hype Cycle for Data Management, four are considered transformational in nature. Two — event stream processing (ESP) and operational in-memory database management system (IMDBMS) — are expected to reach the Plateau of Productivity within two to five years, while both Blockchain and distributed ledgers are expected to take five to 10 years to get to the same point.
ESP
ESP is one of the key enablers of digital business, algorithmic business and intelligent business operations. ESP technology, including distributed stream computing platforms (DSCPs) and event processing platforms (EPPs), is maturing rapidly. Stream analytics provided by ESP software improves the quality of decision-making by presenting information that could otherwise be overlooked.
Operational IMDBMS
Operational IMDBMS technology is maturing and growing in acceptance, although the infrastructure required to support it remains relatively expensive. Another inhibitor to the growth of operational IMDBMS technology is the need for persistence models** that support the high levels of availability required to meet transaction SLAs. Nevertheless, operational IMDBMSes for transactions have the potential to make a tremendous impact on business value by speeding up data transactions 100 to 1,000 times.
Blockchain
Public distributed ledgers, including Blockchain whose technology is derived from the Bitcoin stack, continue to have high visibility says Gartner, although organisations remain cautious about the future of public (permission-less) distributed ledger concepts due to scalability, risk and governance issues. Most business use cases have yet to be proven and extreme price volatility in Bitcoin persists.
Presupposing the technical and business challenges of distributed ledgers can be overcome; in the short term, organisations are most likely to use distributed ledger for operational efficiency gains via the use of shared information and infrastructure. Longer term, Gartner expects a complete reformation of whole industries and commercial activity as the programmable economy develops and ledgers contribute to the monetisation of new ecosystems.
Distributed ledgers
The requirements for more standards and enterprise-scale capabilities are evolving slowly, but distributed ledgers are still not adoptable in a mission-critical at-scale context. Their value propositions, compared with existing technology, are also not clearly established, making the widespread acceptance of the technology problematic. Private distributed ledger concepts are gaining traction, because they hold the promise to transform industry operating models and overcome some of the issues of scalability, risk management and governance that plague public ledgers. As with Blockchain, however, many business use cases are unproven at this time, Gartner said.
Gartner Hype Cycles are a methodology that represent the maturity and adoption of technologies and applications. Emerging technologies begin at the Innovation Trigger part of the Hype Cycle, and as they become touted as the answer to all ills, move up the Peak of Inflated Expectations. Disappointment is inevitable, which Gartner describes as falling into the Trough of Disillusionment. As customers start to separate the wheat from the chaff and see that there can be some benefits to the technology, they have reached the Slope of Enlightenment. Technologies along the Slope of Enlightenment are potentially relevant to solving real business problems and exploiting new opportunities. The technology is mature once it reaches the Plateau of Productivity.
Interested?
Gartner clients can learn more in the report Hype Cycle for Data Management 2017. This research is part of the Gartner Trend Insight Report 2017 Hype Cycles Highlight Enterprise and Ecosystem Digital Disruptions.
Blockchain
Public distributed ledgers, including Blockchain whose technology is derived from the Bitcoin stack, continue to have high visibility says Gartner, although organisations remain cautious about the future of public (permission-less) distributed ledger concepts due to scalability, risk and governance issues. Most business use cases have yet to be proven and extreme price volatility in Bitcoin persists.
Presupposing the technical and business challenges of distributed ledgers can be overcome; in the short term, organisations are most likely to use distributed ledger for operational efficiency gains via the use of shared information and infrastructure. Longer term, Gartner expects a complete reformation of whole industries and commercial activity as the programmable economy develops and ledgers contribute to the monetisation of new ecosystems.
Distributed ledgers
The requirements for more standards and enterprise-scale capabilities are evolving slowly, but distributed ledgers are still not adoptable in a mission-critical at-scale context. Their value propositions, compared with existing technology, are also not clearly established, making the widespread acceptance of the technology problematic. Private distributed ledger concepts are gaining traction, because they hold the promise to transform industry operating models and overcome some of the issues of scalability, risk management and governance that plague public ledgers. As with Blockchain, however, many business use cases are unproven at this time, Gartner said.
Gartner Hype Cycles are a methodology that represent the maturity and adoption of technologies and applications. Emerging technologies begin at the Innovation Trigger part of the Hype Cycle, and as they become touted as the answer to all ills, move up the Peak of Inflated Expectations. Disappointment is inevitable, which Gartner describes as falling into the Trough of Disillusionment. As customers start to separate the wheat from the chaff and see that there can be some benefits to the technology, they have reached the Slope of Enlightenment. Technologies along the Slope of Enlightenment are potentially relevant to solving real business problems and exploiting new opportunities. The technology is mature once it reaches the Plateau of Productivity.
Gartner clients can learn more in the report Hype Cycle for Data Management 2017. This research is part of the Gartner Trend Insight Report 2017 Hype Cycles Highlight Enterprise and Ecosystem Digital Disruptions.
Gartner analysts will provide additional analysis on data and analytics leadership trends at the Gartner Data & Analytics Summits, including on February 26-27, 2018 in Sydney, Australia.
*Previously titled Hype Cycle for Information Infrastructure, 2016, Hype Cycle for Data Management, 2017 covers the broad aspects and technologies that describe, organise, integrate, share and govern data.
*Previously titled Hype Cycle for Information Infrastructure, 2016, Hype Cycle for Data Management, 2017 covers the broad aspects and technologies that describe, organise, integrate, share and govern data.
**Persistence models are those in which previous versions can still be accessed even after the data structure has been modified. A simple analogy would be when "track changes" is switched on in Microsoft Word, allowing all changes to the original text to be seen and rejected.
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