15 "True" Streaming Analytics Platforms For Real-Time Everything

Mike Gualtieri

Streaming Analytics Captures Real-Time Intelligence

Streaming AnalyticsMost enterprises aren't fully exploiting real-time streaming data that flows from IoT devices and mobile, web, and enterprise apps. Streaming analytics is essential for real-time insights and bringing real-time context to apps. Don't dismiss streaming analytics as a form of "traditional analytics" use for postmortem analysis. Far from it —  streaming analytics analyzes data right now, when it can be analyzed and put to good use to make applications of all kinds (including IoT) contextual and smarter. Forrester defines streaming analytics as:

Software that can filter, aggregate, enrich, and analyze a high throughput of data from multiple, disparate live data sources and in any data format to identify simple and complex patterns to provide applications with context to detect opportune situations, automate immediate actions, and dynamically adapt.

Forrester Wave: Big Data Streaming Analytics, Q1 2016

To help enterprises understand what commercial and open source options are available, Rowan Curran and I evaluated 15 streaming analytics vendors using Forrester's Wave methodology. Forrester clients can read the full report to understand the market category and see the detailed criteria, scores, and ranking of the vendors. Here is a summary of the 15 vendors solutions we evaluated listed in alphabetical order:

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Streaming Analytics Will Transform The Internet Of Things Into The Internet Of Analytics

Rowan Curran

The challenges of how to manage, ingest, store, analyze, and act upon data in the IoT are beginning to bear down on enterprises. The honeymoon talk of ‘billions and billions of devices’ is over and it’s time to get down to the dirt of how to generate value from all these connected devices. Streaming analytics platforms, already architected to handle IoT data as it streams into the data center, are being extended to deploy out to gateway devices (such as wireless access points) and even out to edge devices (such as manufacturing equipment) to extend the intelligence out to where data is generated and actions occur.

Forrester clients can read the full details of our analysis here and start the process of turning slow processes and weekly analytical batches into the immediate insights needed to support today’s dynamic business environment.

Hadoop, Spark, and the emerging big data landscape

Paul Miller

Not very long ago, it would have been almost inconceivable to consider a new large-scale data analysis project in which the open source Apache Hadoop did not play a pivotal role.

Every Hadoop blog post needs a picture of an elephant. (Source: Paul Miller)

Then, as so often happens, the gushing enthusiasm became more nuanced. Hadoop, some began (wrongly) to mutter, was "just about MapReduce." Hadoop, others (not always correctly) suggested, was "slow."

Then newer tools came along. Hadoop, a growing cacophony (innacurately) trumpeted, was "not as good as Spark."

But, in the real world, Hadoop continues to be great at what it's good at. It's just not good at everything people tried throwing in its direction. We really shouldn't be surprised by this. And yet, it seems, so many of us are.

For CIOs asked to drive new programmes of work in which big data plays a part (and few are not), the competing claims in this space are both unhelpful and confusing. Hadoop and Spark are not, despite some suggestions, directly equivalent. In many cases, asking "Hadoop or Spark" is simply the wrong question.

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Age Of The Customer Drives Investment In Business Intelligence Tools

Jennifer Adams

In the age of the customer, customer-obsessed firms serious about personalizing customer experience invest in business intelligence (BI) and analytics tools.  Companies collect more and more data on their clients today. BI software is increasingly important to extract information from the raw data, revealing insights. Analytics software tools go beyond traditional reporting and analysis to anticipate customer behavior and provide real-time insights.

In our recently published Business Intelligence And Analytics Software Forecast (Global), 2015 to 2020, we take a more in-depth look at the market’s growth potential. We expect the global BI and analytics software market to grow at a 12% CAGR over the 2015 to 2020 period.

The traditional BI market has matured, but still offers a significant growth opportunity. While business intelligence software is not a new product, Forrester projects robust growth for the solution. As we move into the Internet of Things era, an exponential increase in the number of connected devices will drive demand for BI software tools to understand the information. We expect the BI software market to grow at a 9% CAGR over the forecast period.

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