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Brian Aker On the Future of Databases
blackbearnh recommends
an interview with MySQL Director of Technology Brian Aker that O'Reilly Media is running. Aker talks about the merger of MySQL with Sun, the challenges of designing databases for a SOA world, and what the next decade will bring as far as changes to traditional database architecture. Audio is also available. From the interview: "I think there's two things right now that are pushing the changes... The first thing that's going to push the basic old OLCP transactional database world, which... really hasn't [changed] in some time now — is really a change in the number of cores and the move to solid state disks because a lot of the... concept around database is the idea that you don't have access to enough memory. Your disk is slow, can't do random reads very well, and you maybe have one, maybe eight processors but... you look at some of the upper-end hardware and the mini-core stuff,... and you're almost looking at kind of an array of processing that you're doing; you've got access to so many processors. And well the whole story of trying to optimize... around the problem of random I/O being expensive, well that's not that big of a deal when you actually have solid state disks. So that's one whole area I think that will... cause a rethinking in... the standard Jim Gray relational database design."
I couldn't... agree... more... I'd say that some... very valid... points... have been... raised.
Can we please have another loud, circular debate over which database is best? It's the only way your favorite database will ever win.
Thank you.
Gotta love that link between the hardware limitations and the software concepts that may seem fancy but are essentially only built to get around them. I believe someone once called it "the law of leaky abstractions" - would be interesting to see what the new limitations would be if you start combining solid-state storage with pervasive multiprocessing, i.e. what can you do with a multi-processor multi-sdd server that you can not do with a single-processor single-hard drive server?
I think TFA is pretty right on the money that parallellization and massive use of SSD could cause some pretty fundamental changes in how we approach database optimization - if I were to imagine that rack that I'm staring at being filled with SSD drives and processors instead of with nothing but hard drives... locality of data takes on a whole new meaning if you don't require data to be on the same sector of the HD, but rather want certain sets of data to be stored on storage chips located around the same processor chips to avoid having to overload your busses.
Then again, I haven't been in this game for so long, so maybe I'm overestimating the impact. Oldtimer opinion would be very welcome.
MySQL has people who are responsible for *designing* it? I'm shocked, Shocked.
If moderation could change anything, it would be illegal.
It's more accurate to say that there will probably always be a tradeoff between slow and fast storage, there will probably always be a tradeoff between permanent and temporary storage, and there will probably always be a tradeoff between expensive and cheap storage.
In 20 years, I do not know what form slow, or cheap, or permanent storage may take. It may not be spinning magnetized platters. But I do know that in 20 years, every well-written database will have algorithms and data structures to deal with slow storage, permanent storage, and cheap storage.
I recently blogged on this, but essentially, as long as your average PHP developer thinks of MySQL as a glorified flat file system to place their serialized PHP objects, an always-available, pay-as-you-go distributed database is going to revolutionize application development in the coming years. For those that want to keep control of their data, HBase is coming along quite nicely.
Umm I'd say you have it wrong - "Traditional" databases have many different lock granularities, such as Table locks, page locks and row locks. SQL server and Oracle certainly do this.
MySQL only does table locks, which are much simpler and much faster for light workloads, but as I'm sure you can imagine when you have many CPUs trying to update the table at once in the end each thread has to wait their turn to grab the lock and perform their updates sequentially.
In SQL Server, Oracle, or any other "enterprisey" db multiple threads can update the same table at exactly the same time, as long as its not the same row.
Stuff like this is exactly why people who use MS-SQL and oracle look down their nose at people who use MySQL and claim it is capable of playing with the big boys.
Once again, despite what MySQL are saying there is nothing innovative here. All this stuff has existed in the mainstream database engines for many, many years and they are still playing catchup.
What you say is true for MyISAM tables, but MySQL's InnoDB tables fully support row-level locking. And I believe their BDB tables support page-level locking.
If I was migrating away from Oracle, MS SQL Server wouldn't be my first choice. Postgresql would. Given the choice between a free version that is similar to the original vs a product that is very different that I need to pay for it's a no brainer. Also take into consideration that for some database applications you're going to need some serious horsepower. You're limited in the number of procs you can have in a Windows system. Last time I checked, once you get past 8 processors Windows doesn't scale as well. Even linux doesn't do as well as Solaris, AIX or HPUX past a certain number of procs.
Oracle's RAC seems to be a better solution than MSSQL's approach. PostgreSQL (and EnterpriseDB) are working on a more RAC-like approach.
This is a good story about a company that successfully moved from Oracle to Postgresql. Basically, they had 2 database systems running Oracle, a data warehouse and an OLTP system. They moved their data warehouse over to Postgresql running on Solaris 10, then they used the licenses they no longer need for the data warehouse to boost the computing power of the OLTP system.
Open Source Java DAO Generator
"sudo" is that command which grants one user authorization to act as another user.
"pseudo-" is that verbal prefix which means "false".
I'm seeing language devolve in front of my eyes...
In my mind as a database engineer for a wall street bank, the biggest change in the near term that we forsee is data locality.
Given the amount of computing power on hand today, it may surprise many how difficult it is to engineer a system capable of executing more than a few thousand transactions per second per thread.
Why? Latency. Consider your average SOA application which reaches out to 4-5 remote services or dataserver calls to execute its task. Each network/rpc/soap/whatever call has a latency cost of anything between one and at worst several hundred milliseconds. Lets say for example that the total latency for all the calls necessary is 10 milliseconds. 1000/10=100 transactions per thread per second. Oh dear.
The amount of memory an "average" server ships with today is in the 32-64GB range. Next year it will be in the 64-128GB range. The average size of an OLTP database is 60-80GB.
So, the amount of memory available to the application tier will very soon be greater than the size of the database, warehouses excluded. Moore's law is quickly going to give the application tier far more memory than it needs to solve the average business state, exceptions noted.
The final fact in the puzzle is that for transaction processing, read operations outnumber write operations by roughly 20 to 1. (This will of course vary on the system, but that *is* the average.)
This situation is strongly in favor in migrating read only data caches back into the application tier, and only paying for the network hop when writes are done in the interests of safety. (There is a lot of research into how writes can be done safely asynchronously at the moment, but its not ready yet IMHO.)
Challenges exist in terms of efficient data access and manipulation when caches are large, performant garbage collection and upset recovery - but they are all solvable with care.
Its my opinion that in the near future large data caches in the application tier will become the norm. What has to be worked out is the most effective way of accessing, manipulating and administering that data tier and dealing with all the inevitable caveats of asynchronous data flow.
Some (not complete) examples of implementing this:
Relational Caches (there are many more):
http://www.oracle.com/technology/products/coherence/coherencedatagrid/coherence_for_java.html
http://www.alachisoft.com/ncache/index.html
Object Caches:
http://www.ogf.org/OGF21/materials/970/GigaSpaces_DataGrid_OGF_Oct07.ppt
http://jakarta.apache.org/jcs/
Until recently, solid state storage devices have been treated as "disks". But they're not disks. They have orders of magnitude less latency.
For files, this doesn't matter all that much. For databases, it changes everything. Solid state devices need new access mechanisms; I/O based seek/read/write is oriented towards big blocks and long latencies. The optimal access size for solid state storage devices is much smaller, more like the size of a cache line. With smaller, lower latency accesses, you can do more of them, instead of wasting channel bandwidth reading big blocks to get some small index item. It's not RAM, though; these devices usually aren't truly random access.
It starts to make sense to put more lookup-type functions out in the disk, since getting the data into the CPU has become the bottleneck. Search functions in the disk controller went out of fashion decades ago, but it may be time to bring them back. It may make sense to put some of the lower-level database functions in the disk controller, at the level of "query with key, get back record". Cacheing at the disk controller definitely makes sense, and it will be more effective if it's for units smaller than traditional "disk blocks"
This could be the beginning of the end of the UNIX "everything is a stream of bytes" model of data storage. We may see the "database is below the file system" model, which has appeared a few times in mainframes, make it to ordinary servers.
Had to comment, the reference to Jim Gray was a little weird? I was lucky to work with Jim and we were often talking about technology changes and enhancements. Now - see what for example Tandem did call "massively parallel" database! The system was already built to allow several cpus and several nodes to interconnect transparently, Jim did see how that could be used and how the database optimizer really could work. Of course making direct access to any disc faster will help, especially now when the SDD's are getting bigger but the theory is nothing new. Even SQLite can show you that and think systems where you have 32, 128 or even 256 bit flat, memory speed but storage backed world - will change the picture, or? But be careful, we have already gone through many iterations making part of the system faster, as fixed head disks and even indexing in solid state, and found that it may (will) create other problems, not always seen upfront (except by JG!)