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High Availability Solutions for Databases?
An anonymous reader asks: "What would be the best high availability solution for databases? I don't have enough money to afford Oracle RAC or any architecture that require an expensive SAN. What about open source solutions? MySQL cluster seems to be more master/slave and you can lose data when the master dies. What about this Sequoia project that seems good for PostgreSQL and other databases? Has anyone tried it? What HA solution do you use for your database?"
While MySQL supports master/slave replication, MySQL Cluster specifically avoids that entire model. It's an entirely synchronous database storage engine. If you want master/slave, use postgres. If you want high availability and can handle the lack of a small number of features, MySQL Cluster is the way to go. The only real downside to the architecture required for CLuster is that all of the data is stored in RAM based tables. transactions are logged to disk every (configurable) time interval. If you're going to try for HA, you might want to RTFM on the available options before you settle on one.
It's odd that all these people are answering without hearing a thing about your application. How big is the db? How often is it written? How often is it read?
For example, we run a site with data from a thousand odd different data sources, with each source getting updated every hour or so. We do it by parsing the data into static pages. We we receive a datum, we rebuild the pages that depend on it.
We have another site that runs off an Oracle db. the static page site runs about 90x faster, and is basically in memory (disk access is nil.) Now take into account that we can (and do) replicate the static page solution with zero load, we get to a solution that is literally 900x faster.
Now folks are thinking 'oh, the horror!' well... tough! There is no substitute for thinking about your data, and how it flows. A DB is not a given, but a (potentially wrong) answer to a question after you have done some analysis.
Hello, anonymous Sequoia promoter seeking free advertising. (BTW, You might try picking a product name that normal people can spell without thinking about it).
Your solution is not database clustering, and should not be advertised as such. It's more a long the lines of a database connection proxy which supports multiple simultaneous backends and operating on them in parallel, with some added features to make HA-like solutions relatively easy.
The downside of this style of approach, as opposed to an architecture of the likes of Oracle "RAC", is that it doesn't scale up as you add backend nodes (at least not for writes, but in any case for read-only scaling there are simpler solutions for all of the vendors, even the free ones), and it must have limits on how many transactions it can backlog and replay to a temporarily-unreachable/down server before that server has to be re-synced from scratch in order to catch back up (and I have to wonder if there's really any real-world scenario under real transaction load in which the practical net effect wouldn't be a complete resync of a backend server anytime something goes wrong with it, in which case one could throw out any attempt to backlog transactions for a single failed server and just keep things simple - you fall out of sync, you resync).
The open source world really needs a RAC-like solution for PostgreSQL and MySQL (I'm a fan of friendly open-source competition, so while my personal preference is PostgreSQL, I hope both projects stay current and popular for many years to come). Unfortunately there is unlikely to be a generic way to do this, it will probably have to be re-invented for each database project.
I took a brief look around PostgreSQL's guts a while back, and it actually seemed like the architecture they use isn't far off from something RAC-capable to begin with, just nobody's quite buttoned together a few peices here and there to make it happen. Basically on SMP multiple co-operating backends already serve parallel requests and synchronized on a shared memory cache. There's patches out there for the linux kernel to support network-synchronized distributed shared memory. Put two and two together, and what do you get? Something not far off from a first-pass hack at a RAC-like network-distributed database caching system. Most of the other details are easy to solve (start/shutdown, join/leave cluster, tracking of processes across the cluster, etc), or belong in another problem domain (implementing shared storage filesystems (hey, we have GFS, Oracle OCFS, etc available...)). One of the biggest issues would be multiple nodes all having pg "Writer" processes. The first step would probably be to put the writer on one node and failover the writer functionality when that node dies, to be quickly replaced by a scheme whereby multiple writers can work by synchronizing through a distributed lock manager (there are already dlm modules available for linux). Then there's the issue of making the current distributed shared-memory patches do the right thing performance-wise for this kind of usage, and so on. It's not easy, but it's not outside the realm of possibility.
11*43+456^2
The submitter of this question seems to have confused the two, Cluster and the older replication. Cluster does not in any way rely on a master/slave setup. Think of Cluster as RAID for databases, where you can lose a node (or more, depending on your configuration) before you lose your db. The current drawbacks of cluster are that it is in-memory and doesn't support certain features, such as fulltext indexing. Replication isn't going to cause you to lose data either if your application is designed to handle a situation where the master server (which you kick your writes to) hits the bricks. Have the app go into a read only mode from your slave.
Neither option is really "beautiful", though Cluster has a lot of promise for the future, especially in 5.1.