High-performing memory throws many traditional decisions overboard
Over the past decade, SSD drives (popularly known as Flash) have radically changed computing at both the consumer level — where USB sticks have effectively replaced CDs for transporting files — and the server level, where it offers a price/performance ratio radically different from both RAM and disk drives. But databases have just started to catch up during the past few years. Most still depend on internal data structures and storage management fine-tuned for spinning disks.
Citing price and performance, one author advised a wide range of database vendors to move to Flash. Certainly, a database administrator can speed up old databases just by swapping out disk drives and inserting Flash, but doing so captures just a sliver of the potential performance improvement promised by Flash. For this article, I asked several database experts — including representatives of Aerospike, Cassandra, FoundationDB, RethinkDB, and Tokutek — how Flash changes the design of storage engines for databases. The various ways these companies have responded to its promise in their database designs are instructive to readers designing applications and looking for the best storage solutions.
Competition, access to bandwidth, and other issues muddy the net neutrality waters.
It was the million comments filed at the FCC that dragged me out of the silence I’ve maintained for several years on the slippery controversy known as “network neutrality.” The issue even came up during President Obama’s address to the recent U.S.-Africa Business forum.
Most people who latch on to the term “network neutrality” (which was never favored by the experts I’ve worked with over the years to promote competitive Internet service) don’t know the history that brought the Internet to its current state. Without this background, proposed policy changes will be ineffective. So, I’ll try to fill in some pieces that help explain the complex cans of worms opened by the idea of network neutrality.
Buildings are ready to be smart — we just need to collect and monitor the data.
Buildings, like people, can benefit from lessons built up over time. Just as Amazon.com recommends books based on purchasing patterns or doctors recommend behavior change based on what they’ve learned by tracking thousands of people, a service such as Clockworks from KGS Buildings can figure out that a boiler is about to fail based on patterns built up through decades of data.
I had the chance to be enlightened about intelligent buildings through a conversation with Nicholas Gayeski, cofounder of KGS Buildings, and Mark Pacelle, an engineer with experience in building controls who has written for O’Reilly about the Internet of Things. Read more…
Business models and sustainability will drive success in the health games space.
These efforts have born fruit, and clinical trials have shown the value of many such games. Ben Sawyer, who founded the Games for Health conference more than 10 years ago, is watching all the pieces fall into place for the widespread adoption of games. Business plans, platforms, and the general environment for the acceptance of games (and other health-related apps) are coming together.
Find emergent properties and solutions to new computing problems with graphs
Graph databases haven’t made the news much because, I think, they don’t fit in convenient categories. They certainly aren’t the relational databases we’re all familiar with, nor are they the arbitrary keys and values provided by many NoSQL stores. But in a highly connected world–where it’s not what you know but whom you know–it makes intuitive sense to arrange our knowledge as nodes and edges.
Ted Nelson, inventor of the hyperlink, recognized the power of viewing life in graphs. After the implosion of his historic Xanadu project, he embarked on a graph database tool called ZigZag. The most modern instantiations of graphs–the Neo4j store and the Alchemy.js tool for interactively visualizing graphs–were well represented this year at O’Reilly’s Open Source convention.
Can education and peer review keep a huge open source project on track?
When does a software project grow to the point where one must explicitly think about governance? The term “governance” is stiff and gawky, but doing it well can carry a project through many a storm. Over the past couple years, the crucial OpenStack project has struggled with governance at least as much as with the technical and organizational issues of coordinating inputs from thousands of individuals and many companies.
A major milestone was the creation of the OpenStack Foundation, which I reported on in 2011. This event successfully started the participants’ engagement with the governance question, but it by no means resolved it. This past Monday, I attended some of the Open Cloud Day at O’Reilly’s Open Source convention, and talked to a lot of people working for or alongside the OpenStack Foundation about getting contributors to work together successfully in an open community. Read more…
Internet of Things, local energy sources, and online collaboration underlie the Zero Marginal Cost Society.
More visible at Health Privacy Summit than Health Datapalooza.
On the first morning of the biggest conference on data in health care–the Health Datapalooza in Washington, DC–newspapers reported a bill allowing the Department of Veterans Affairs to outsource more of its care, sending veterans to private health care providers to relieve its burdensome shortage of doctors.
There has been extensive talk about the scandals at the VA and remedies for them, including the political and financial ramifications of partial privatization. Republicans have suggested it for some time, but for the solution to be picked up by socialist Independent Senator Bernie Sanders clinches the matter. What no one has pointed out yet, however–and what makes this development relevant to the Datapalooza–is that such a reform will make the free flow of patient information between providers more crucial than ever.
Bio-IT World shows what is possible and what is being accomplished
If your data consists of one million samples, but only 100 have the characteristics you’re looking for, and if each of the million samples contains 250,000 attributes, each of which is built of thousands of basic elements, you have a big data problem. This is kind of challenge faced by the 2,700 Bio-IT World attendees, who discover genetic interactions and create drugs for the rest of us.
Often they are looking for rare (orphan) diseases, or for cohorts who share a rare combination of genetic factors that require a unique treatment. The data sets get huge, particularly when the researchers start studying proteomics (the proteins active in the patients’ bodies).
So last week I took the subway downtown and crossed the two wind- and rain-whipped bridges that the city of Boston built to connect to the World Trade Center. I mingled for a day with attendees and exhibitors to find what data-related challenges they’re facing and what the latest solutions are. Here are some of the major themes I turned up.