Inside Analysis

10 Companies and Technologies to Watch in 2016

Each year we highlight 10 companies and technologies to watch. The selection we make is from companies that have briefed us about their technology in the previous year, which means that we are reasonably familiar with their products and what they can achieve. We choose companies and technologies that are distinctive, innovative and in line with what we consider to be the general direction of the IT industry. Consequently, there should be no surprise that this year’s list includes quite a few big data and/or analytics products. However, other technologies we regard as groundbreaking are also included.

As usual, the list is arranged in alphabetical order by product to avoid any suggestion that we have ranked the products in any way.

  • Blazegraph from SYSTAP: Blazegraph is a highly scalable and highly performant graph database. In our view, the analytical exploitation of graph data is still fairly nascent. The analysis of non-graph data is a relatively well traveled path, whereas the analysis of graph data is in its infancy to some degree. This is especially the case in respect to very large volumes of graph data. Blazegraph is exactly the kind of engine that can open up this field of analytics. It can analyze graph data with millions, billions and even trillions of edges in the graph, processing billions of edges in milliseconds. The product gets its remarkable speed from its ability to exploit GPU technology.
  • Diaku Axon: You may be inclined to think of Diaku Axon as a second generation data governance product. The first generation of data governance products were the result of a variety of dynamics: regulatory requirements, MDM initiatives, risk management, etc. The second generation is far less fragmented. It is about integrating the whole collection of activities. And it is perhaps worth adding that the explosion of analytics applications has expanded the need and the range of what was originally thought of as data governance to include data provenance and lineage. Diaku Axon brings it all together: data definitions, business level glossaries, governance policies, compliance, collaboration among data users, data lineage and even data usage statistics information. It’s integrated into a coherent whole.
  • Diyotta: With the advent of Hadoop, it was likely there’d be a new big data-oriented data integration product. That pretty much explains Diyotta. The product/platform uses both Hadoop and the Spark engine, effectively turning Hadoop into an information hub that can spray out data to any application that requires it. It’s a natural fit for those who need to integrate new Hadoop data heaps with old data warehouses, mainly because it was built for hybrid environments. In our view, the IT world is coming to depend more and more on data flows. As such, Diyotta is a data flow platform.
  • Eureqa from Nutonian: One clear trend in 2015 was the emergence of analytics products that reduce the need for data science expertise. With data science skills at a premium, it was inevitable that some products of this ilk should appear. The one that caught our attention most was Eureqa from Nutonian. Eureqa automates a great deal of the manual activity involved in analytics, using a fair amount of smarts (automated evolutionary algorithms) to create predictive models at speed – in minutes. The neat thing about Eureqa is that it spans the user range from business analyst to genuine data scientist and describes the analytical models it builds in easily understood English. Take a look.
  • Exaptive: Put simply, Exaptive is a rapid application development platform focused on analytics that can integrate components from all other technologies. You build web-based apps (called Xaps) by integrating components together. The Exaptive Studio provides sets of components and component templates within an intuitive visual development environment. It embodies its own data model, combining it with a service-oriented approach that enable Xaps to access multiple data sets and run large processes without the need for a structured data store like a data warehouse. The company has fostered a collaborative community where its customers share or sell useful components that you can weave into your applications. We expect this to generate a good deal of interest and usage because it eliminates code complexity from analytics applications.
  • Lucidworks Fusion: Fusion is a smart search platform for very large amounts of data, enabling you to design, develop and deploy search apps at any scale. It works hand in hand with Solr. With Hadoop, we’ve noticed great deal of activity to patch in SQL for queries. The natural counterpart to that is a search capability that lets you get at the less structured data that SQL cannot touch. Fusion offers that capability and delivers it intelligently – not in the usual Google fashion. It employs advanced signal processing and machine learning techniques. This is one of those products where it really helps to see a demo. If you feel you have the need, you should probably take a look.
  • Novetta Entity Analytics: If you don’t know what entity analytics is, you probably should. It’s the branch of data analytics that organizes and unifies data entities (like people, products, etc.) to provide a single view. It eliminates ambiguities and provides a coherent reliable picture from all the data available on a given entity.  Imagine you have, say, 20 sources of information on people. It will unite them using a series of intelligent rules that will highlight anomalies in the data that may be due to dirty data or disinformation. What might not be immediately obvious but has proven to be the case is that it enables data analysts to examine and connect data in ways that probably would not have occurred to them otherwise. Its main area of application is in CRM, marketing and fraud reduction. It is particularly effective when used with Hadoop data lakes, which often contain multiple records that apply to a given data entity.
  • Ryft: I had been expecting more hardware-based products to emerge. This was based on the idea that the trend for commodity servers would be counterbalanced by powerful, intelligently-designed hardware. We haven’t seen much of this, but luckily what we have seen is impressive. Ryft is a query engine, pure and simple. It takes data, a great deal of it, and throws queries at the data, providing lightning fast answers. When we say “lightning fast,” we mean it. A single Ryft server can preside over 50 terabytes of data and will resolve complex queries in millseconds. The trick is that the data is stored as ingested, as bits, and the data is searched by bit pattern using a bank of FPGA processors. Ryft can legitimately claim to be a Hadoop alternative, but it is broader than that. It can query any data: video, images, sound, holograms, whatever.
  • Springpath Data Platform: If you can virtualize servers, why not virtualize all file systems, turning them into a global file system available to all? That’s what Springpath does with its Data Platform. The company was created by developers from VMware, who, we presume, were looking for something new to virtualize. So they developed what they now describe as a Single Hyperconverged Data Platform which can straddle any number of commodity servers, including those that have been partitioned into virtual servers running any OS you care for, and provide a data platform beneath it. In our view, this technology has legs.
  • Snowflake Computing: None of the databases we encountered in 2015 made this list, but Snowflake Computing with its Elastic Data Warehouse did. OK, it has some seriously fast and unique database technology, but what it provides is a Cloud Data Warehouse as a Service. There’s a lot to love about this. Data warehouse in the cloud is a neat proposition on its own, if it means that you can reduce or eliminate a good deal of the data warehouse labor and pain. But add elasticity (scale data volumes up or down on demand), the ability to accommodate unstructured as well as structured data and a very high speed engine, and you have something that is going to appeal to pretty much every segment of the market.

In truth, all of these companies are worth looking at, even if you have no need for the technology, because every one is moving the needle in one way or another.

Robin Bloor

About Robin Bloor

Robin is co-founder and Chief Analyst of The Bloor Group. He has more than 30 years of experience in the world of data and information management. He is the creator of the Information-Oriented Architecture, which is to data what the SOA is to services. He is the author of several books including, The Electronic [email protected], From the Silk Road to the eRoad; a book on e-commerce and three IT books in the Dummies series on SOA, Service Management and The Cloud. He is an international speaker on information management topics. As an analyst for Bloor Research and The Bloor Group, Robin has written scores of white papers, research reports and columns on a wide range of topics from database evaluation to networking options and comparisons to the enterprise in transition.

Robin Bloor

About Robin Bloor

Robin is co-founder and Chief Analyst of The Bloor Group. He has more than 30 years of experience in the world of data and information management. He is the creator of the Information-Oriented Architecture, which is to data what the SOA is to services. He is the author of several books including, The Electronic [email protected], From the Silk Road to the eRoad; a book on e-commerce and three IT books in the Dummies series on SOA, Service Management and The Cloud. He is an international speaker on information management topics. As an analyst for Bloor Research and The Bloor Group, Robin has written scores of white papers, research reports and columns on a wide range of topics from database evaluation to networking options and comparisons to the enterprise in transition.

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