Databases
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    <p>Database scalability is a VERY complicated issue; there are a LOT of issues that come into the whole process.</p> <p>First, consider the lowest-hanging fruit; do you have individual tables (or columns) that are going to be containing the bulk of your data? Columns which will contain BLOBs which are > 4MB each? Those can be extracted from the database and stored on a flat-file storage system, and merely referred to from the database; right there, that can take many unwieldy solutions down to a manageable level.</p> <p>If not, do you have deeply different usage patterns for different subgroupings of tables? If so, there's an opportunity right there for segmenting your database into different functional databases which can be partitioned onto different servers. A good example of this is read-mostly data, such as on webservers, which gets generated rarely (think user-specific home page data), but read frequently; that type of data can get segregated into a database (or, again, flatfile with references) that's separate from the rest of the user data).</p> <p>Consider the transactional requirements of your database; can you isolate your transaction boundaries cleanly, or will there be deeply mingled transactions going on all through your database? If you can isolate your transaction boundaries, there's another potential useful boundary.</p> <p>This is just touching on some of the issues involved with this sort of thing. One thing worth considering is whether or not you really need to have a database that is actually going to be huge, or if you're just trying to use the database as a persistence layer. If you're using the database just as a persistence layer, you might reconsider whether you actually need the relational nature of a database at all, or if you can get away with a smaller relational overlay on top of a simpler persistence layer. (I say this because a large quantity of solutions seem like they could get away with a thin relational layer over a large persistence layer; it's worth considering.)</p>
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    1. USPaul Sonier
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    1. COto give you a little more info on the actual problem at hand, we are going to be extracting large amounts of data from a bunch of sources and parsing tons of statistics from each entry. every day the database will deal with 100,000+ new entries each with 100's of statistics. the actual file size of each entry is prob < 1KB and once its parsed doesn't need to be used. we will then run lots and lots of different queries in real time on the every growing dataset and eventually open up the platform for other people to do the same.
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      1. USLuke Belbina
    2. CO@nextgenneo: yeah, you DO have a bit of a problem there. I'd still recommend doing what you can to sensibly partition your database; is there some sort of temporal horizon across which you won't be crossing, or the like? Because if you really do have a large, unpartitionable relational dataset, you may need to end up going with a (very expensive) commercial solution. I'm no fan of Oracle (to say the least), but they understand epic scaling better than anybody.
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