In the second quarter of 2014, new de facto standards emerged and galvanized, major cloud providers launched new analytics offerings, and mainstream databases began to take on attributes and capabilities of heretofore separate special-purpose products.
Thus is the paradox of the data analytics market right now. New techniques and technologies emerge, but things are nonetheless becoming more integrated. This extends to companies too as the venture capital dollars continue to flow in, but at the same time, a few acquisitions presage a consolidation for the industry.
This report will examine the following areas of activity this quarter and their impact on the near-term outlook in the analytics space:
- Funding rounds were closed by all three major Hadoop vendors, and there were also smaller rounds by companies in the in-memory analytics and business intelligence spheres. Vendors are still going back to the well, and self-sufficiency is a ways off.
- Several acquisitions, also spanning the field of Hadoop players and business intelligence competitors, took place this quarter. Consolidation is starting to take root.
- Each of the three major public cloud providers have either shored up analytics offerings or announced entirely new ones. The cloud, as a data analytics platform, may be belatedly blooming, with customers’ trepidation subsiding.
- Apache Spark and YARN, two open source projects that are at once different and yet competitive, reached critical mass in vendor support. The fundamental Hadoop stack is changing, and MapReduce’s importance is waning.
- Streaming data processing and machine learning are now on-radar for the broader data analytics marketplace, making this one of the next frontiers for big data and a focus area for vendors.
- Suddenly several transactional databases are integrating analytical capabilities in a quest to serve in mixed-workload capacities. The sprawl of data across multiple databases may be coming to an end.
- Data in the cloud
- Spark and YARN momentum
- The next step for streaming and machine learning
- Transactional/analytical database convergence
- Near-term outlook
- Key takeaways
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