Oracle Pushes Compression to Scale Databases
Taking Data Compression Down to the Block Level
Oracle has offered simple index-level compression since the 8i version of its database was introduced in 1999. That improved several years later with the introduction of table-level compression in Oracle 9i Release 2, which helped data warehousing users compress data for faster bulk loads, according to Sushil Kumar, senior director of product management for database manageability, high availability and performance at Oracle.
Advanced Compression provides even finer capabilities, letting the database compress data down to the disk-block level (download PDF). The algorithm used in the new feature compresses data while keeping track of exactly where information is stored, Kumar said. The result, he claimed, is that when data is extracted by users, the database can focus in like a laser on the exact block on the disk where the information is located, instead of pulling whole tables and sifting through unwanted data.
Other compression schemes "have no idea what's on the disk," Kumar contended. "They can't read part of a document without opening up the entire one."
According to Oracle officials, Advanced Compression is also smart enough not to compress data with every single change to a database, but to instead let the changes accumulate and then run them in batches. That is efficient enough to enable Advanced Compression to work with OLTP databases, which tend to have heavy read/write volumes, said Vineet Marwah, a principal member of the Oracle database staff.
Another component of Advanced Compression, called SecureFiles, can automatically detect, index and compress non-relational data such as Word documents, PDFs or XML files, Marwah said. Oracle also has enhanced its backup compression performance so that it is 40% faster in 11g than in the previous version of the database, while not degrading the performance of other database functions, he said.
And because a compressed database is generally much smaller, it shrinks the flow of data between the storage server and database, where bottlenecks tend to occur, Kumar said. The gains are so dramatic that DBAs can dump their complicated partitioning and archiving schemes, he claimed. "A lot of people archive data because they have to, not because they want to," he said. "So if you see a business value in keeping data around, compression is a useful way to not let resource constraints dictate your architecture."