SSIMWAVE customers – from film producers to network engineers to media business executives – work to some of the highest standards in the world. They demand to work with the best. SSIMWAVE also works at that level, as the company’s 2015 Emmy award for engineering achievement demonstrates. They also ask the same high standards of their technology vendors/partners. For SSIMWAVE’s rather comprehensive analytics needs, only one database makes the grade: SingleStore.
SSIMWAVE has unique technology and unique analytics needs. SSIMWAVE mimics the human visual system, enabling the software to quantify the quality of video streams, as perceived by viewers, into a single viewer score. Video delivery systems can then be architected, engineered, and configured to manage against this score. This score correlates strongly to what actual human beings would perceive the video quality to be. This allows SSIMWAVE users to make informed trade-offs among resources and perceived quality, automatically or manually, and all in real time.
SSIMWAVE Cracks the Code
According to Cisco, video data accounted for 73 percent of Internet traffic in 2017, a share that is projected to grow to 82 percent by 2022. Maximizing the quality of this video content, with the least bandwidth usage and at the lowest cost possible, is one of the most important engineering, business, and user experience issues in the online world.
The barrier to balancing video quality against compression has been that only human beings could accurately assess the quality of a given video segment when it was compressed, then displayed on different devices. Further complicating the picture (no pun intended) is the fact that people, when asked to rate video quality, give different answers with varying levels of consistency over time. This has meant that a panel of several people was needed to render a useful assessment. As a result, a software engineer or operations person wanting to process and deliver data within acceptable levels didn’t have a reliable, affordable method for knowing how much was just enough, without serious compromise to the viewer’s experience.
SSIMWAVE appears to have cracked the code on this problem with its proprietary SSIMPLUS® algorithm, described on their website, which provides capabilities not found elsewhere. The company’s technology assesses video quality with a single, composite number that achieves a correlation greater than 90 percent between machine assessment and subjective human opinion scores. With this technology, video professionals can make much more efficient use of network resources, while consistently maintaining the desired level of quality.
SSIMWAVE users are able achieve significant bandwidth savings by configuring to deliver on a viewer score. The company’s customers include the largest IPTV providers in the US and Canada. Their platform is affecting the streams of tens of millions of subscribers in North America. SingleStore already has a strong position in media and communications solutions, including having Comcast as a customer, and it was natural for SSIMWAVE to consider SingleStore for its own analytics needs.
SSIMWAVE’s Need for State-of-the-Art Analytics
SSIMWAVE’s business is, in the end, all about numbers. For the company to deliver a complete and reliable service, it needs a high-performance database that can store very large quantities of data and respond very quickly to ad hoc analytics queries.
SSIMWAVE has ambitious analytics goals. In addition to comprehensive internal requirements, it needs to offer state-of-the-art analytics capabilities to customers.
SSIMWAVE needs both up-to-the-moment reporting, on data volumes that will increase exponentially as new data streams in, and the ability to retain all that data to meet customer service level agreements (SLAs).
SSIMWAVE Chooses SingleStore
SSIMWAVE was ready for an innovative solution. It compared three technologies that seemed most likely to meet its requirements:
The database assessment was led by Peter Olijnyk, Director of Technology at SSIMWAVE. Peter has 20 years experience as a software developer, architect, and engineering leader, along with a passion for playing guitar in his rock band.
Olijnyk and his team at SSIMWAVE found the choice relatively easy, and decided on SingleStore. Among the key considerations were:
“The main thing that tipped the scales was the ease of use and out-of-box experience,” according to Olijnyk. “We went from reading about SingleStore to having clusters running in a matter of hours.”
“We implement real-time data streaming and SingleStore for ingest and query response,” he reports. “Also, we recently needed a way to share state across our architecture. We considered ZooKeeper and Redis, but we ended up using SingleStore rowstore, because it gives us such high performance.”
The move to this architecture for SSIMWAVE was never far from Olijnyk’s mind. “We prioritize ease of use and ease of installation. We have to concern ourselves with this approach; otherwise, costs and support effort would rise quickly. The fewer technicians we have to manage to support our customers, the better.”
SSIMWAVE Chooses Managed Service
SSIMWAVE was able to move quickly and smoothly into production to provide its service at scale to OTT companies. A few months after deployment, SSIMWAVE moved to SingleStore Managed Service, the new, high-performance, elastic cloud database service. With SingleStore Managed Service, SSIMWAVE gets the same high performance as before, and includes cloud services and software, but with much less operations effort.
“Our focus is to make sure each video stream delivered makes its way to a happy customer. SSIMWAVE tunes video content quality to balance feasibility with the best experience possible.We moved to SingleStore Managed Service, as soon as it was available, because it helps us maintain that focus,” according to Olijnyk. He had cited ease of use and the out-of-the-box experience as drivers in the original move to SingleStore. With SingleStore Managed Service, both ease of use and the out-of-the-box experience are improved further.