If relational databases had just worked at scale to begin with, the IT sector would be a whole lot more boring and we wouldn’t be having a conversation with Andrew Fikes, the vice president and Engineering Fellow at search engine, application, and cloud computing giant Google who has been instrumental in the creation of many of its databases and datastores since joining the company in 2001. …
Many programs have a tough time spanning across high levels of concurrency, but if they are cleverly coded, databases can make great use of massively parallel compute based in hardware to radically speed up the time it takes to run complex queries against large datasets. …
There is much value in separating storage from compute, particular for cloud database deployments. …
In the long run, provided there are enough API pipes into the code, software as a service might be the most popular way to consume applications and systems software for all but the largest organizations that are running at such a scale that they can command almost as good prices for components as the public cloud intermediaries. …
Among all of the hardware and software that is in a datacenter, the database – whether it is SQL, NoSQL, NewSQL or some other contraption in which to pour data and ask questions about it – is probably the stickiest. …
To get straight to the point: nobody wants to have large grain snapshots of data for any dataset that is actually comprised of a continuous stream of data points. …
Artificial intelligence and machine learning, which found solid footing among the hyperscalers and is now expanding into the HPC community, are at the top of the list of new technologies that enterprises want to embrace for all kinds of reasons. …
In many ways, public clouds like Amazon Web Services, Microsoft Azure, and Google Cloud Platform can be the great equalizers, giving enterprises access to computing and storage resources that they may not have the money to be able to bring into their on-premises environments. …
While it is always best to have the right tool for the job, it is better still if a tool can be used by multiple jobs and therefore have its utilization be higher than it might otherwise be. …
There is an arms race in the nascent market for GPU-accelerated databases, and the winner will be the one that can scale to the largest datasets while also providing the most compatibility with industry-standard SQL. …
All Content Copyright The Next Platform