I can explain it, the methods are straightforward. As with most things in database engine design, much of what is done in industry isn't in the literature.
The alternative to VSBs is for each logical index node to comprise a dynamic set of independent fixed buffers, with each buffer having an independent I/O schedule. This enables excellent cache efficiency because 1) space is incrementally allocated and 2) the cache only contains parts of logical node that you actually use. References to the underlying buffers remain valid even if the index node is resized. Designs vary but 8 to 64 buffers per index node seems to be the anecdotal range. The obvious caveat is that storage structures that presume an index node is completely in buffer, such as ordered trees, don't work well. Since some newer database designs have no ordered trees at all under the hood, this is not necessarily a problem. There are fast access methods that work well in this model.
The main issue with VSBs is that it is difficult to keep multiple references to the page consistent, some of which may not even be in memory, since critical metadata is typically in the reference itself. A workaround is to only allow a single reference to a page, but this restriction has an adverse impact on some types of important architectural optimization. The abstract objective makes sense, but no one that has looked into it has come up with a VSB scheme that does not have these tradeoffs for typical design cases. That said, VSBs are sometimes used in specialized databases where storage utilization efficiency (but not necessarily cache efficiency or performance) is paramount, though designed a bit differently than Umbra.
The reason to use larger page sizes, in addition to being more computationally efficient, is that it gives better performance with cheaper solid-state storage -- storage costs matter a lot. The sweet spot for price-performance is inexpensive read-optimized flash, which works far better for mixed workloads than you might expect if your storage engine is optimized for it. Excellent database kernels won't see much boost from byte-addressable NVM and people using poor database architectures don't care enough about performance to pay for expensive storage hardware, so it is a bit of a No Man's Land.
The alternative to VSBs is for each logical index node to comprise a dynamic set of independent fixed buffers, with each buffer having an independent I/O schedule. This enables excellent cache efficiency because 1) space is incrementally allocated and 2) the cache only contains parts of logical node that you actually use. References to the underlying buffers remain valid even if the index node is resized. Designs vary but 8 to 64 buffers per index node seems to be the anecdotal range. The obvious caveat is that storage structures that presume an index node is completely in buffer, such as ordered trees, don't work well. Since some newer database designs have no ordered trees at all under the hood, this is not necessarily a problem. There are fast access methods that work well in this model.
The main issue with VSBs is that it is difficult to keep multiple references to the page consistent, some of which may not even be in memory, since critical metadata is typically in the reference itself. A workaround is to only allow a single reference to a page, but this restriction has an adverse impact on some types of important architectural optimization. The abstract objective makes sense, but no one that has looked into it has come up with a VSB scheme that does not have these tradeoffs for typical design cases. That said, VSBs are sometimes used in specialized databases where storage utilization efficiency (but not necessarily cache efficiency or performance) is paramount, though designed a bit differently than Umbra.
The reason to use larger page sizes, in addition to being more computationally efficient, is that it gives better performance with cheaper solid-state storage -- storage costs matter a lot. The sweet spot for price-performance is inexpensive read-optimized flash, which works far better for mixed workloads than you might expect if your storage engine is optimized for it. Excellent database kernels won't see much boost from byte-addressable NVM and people using poor database architectures don't care enough about performance to pay for expensive storage hardware, so it is a bit of a No Man's Land.