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Cloud-Based and Horizontally Scalable Databases
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As the Internet has developed, many standard elements of the Internet architecture have been faced with the need to massively scale in their ability to process very large volumes of transactions. Web servers must scale to handle millions of clicks per hour. Application servers must scale to execute business logic on behalf of tens of thousands of transactions. Network elements like routers, switches, and load balancers must similarly scale.
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27:
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In each of these cases, the approach to scaling has been horizontal a single web server grows into two, then three, then a dozen, and potentially hundreds of servers sharing the workload in the web-server tier. The servers operate from shared or replicated storage, with each server able to serve up any given page on demand. To make the scheme work, the server is implanted as a stateless system. Whenever possible, any information that must be retained across individual interactions is passed back to the client, to be passed back into the network with the next request. Any state information that cannot be handled in this way is pushed in the other direction back into the database server that underlies the architecture. For many high-volume web sites or web services, the underlying database is now beginning to emerge as a bottleneck. Unfortunately, the horizontal scaling solution that worked so well for web servers and application servers runs into problems for the database server. By its very nature, the database is stateful, not stateless. The ACID (Atomicity, Consistency, Isolation, and Durability) properties demand that either all the individual elements of a transaction are committed or none are committed, and that concurrent transactions should not interfere with one another. There is no back-end layer into which state information can be pushed; the database must maintain the state information. These challenges represent an important new frontier in database architecture designing database systems that can scale horizontally with efficiency. Significant advances have been made in recent years as vendors deployed databases with clustering or grid capability. These new database architectures must clearly spread out the database processing across dozens of servers or more, but the information on those servers must be kept consistent, in all the ways described in 12. Part of the solution will come from intelligently dividing different types of data in the database. Reference or lookup data that does not change, or data that changes only infrequently (such as customer contact information), can be horizontally replicated, because maintaining consistency across dozens of servers does not require much effort. Transitive data, such as the data maintained during the course of a transaction, will probably need to be maintained on a single system of record within the cluster of systems, with requests for that data being automatically routed to the correct system. How to deliver this architecture in an efficient, scalable manner remains a new frontier for commercial products. But the demand for databases that can reside in the cloud and deliver massive scalability using horizontal scaling techniques is substantial and growing. Startup vendors that present a plausible way of building such systems will attract venture funding, and the techniques that emerge to successfully address the problem will eventually find their way into mainstream products, as others have before them. When that happens, database processing power delivered in the cloud, the way massive computing power and storage are being delivered today, can become a reality.
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PART VI
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Part VI:
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SQL continues to play a major role in the computer industry and appears poised to continue as an important core technology: SQL-based databases are flagship software products for the three largest software vendors in the world: Microsoft, Oracle, and IBM. SQL-based databases operate on all classes of computer systems, from mainframes and database servers to desktop computer clients, notebook computers, and handheld PDAs. All of the major enterprise applications used in large organizations rely on enterprise-class SQL databases to store and structure their data. SQL-based databases have responded successfully to the challenges of the object model, with SQL extensions in object/relational databases. SQL-based databases are responding to the needs of Internet-based architectures by incorporating XML and integrating tightly with application servers. Providing massive database scalability for cloud computing is a major challenge confronting the database market today.
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