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Are Relational Databases Obsolete?
jpkunst sends us to Computerworld for a look at Michael Stonebraker's opinion that RDBMSs "should be considered legacy technology." Computerworld adds some background and analysis to Stonebraker's comments, which appear in a new blog, The Database Column. Stonebraker co-created the Ingres and Postgres technology while a researcher at UC Berkeley in the early 1970s. He predicts that "column stores will take over the [data] warehouse market over time, completely displacing row stores."
Relational databases aren't being obsoleted. Some schema design heuristics are.
0xfeedface
every article linked makes it clear that this is about warehousing as opposed to oltp. so is the technology dead? no - can it do everything? no
It's hard to believe that's how Micronians are made. Why don't we see it right now by having you both kiss one another?
The most recent release (2007) will handle 2^14 columns.
"Sacrifice for the good of The State" - The State
Once someone shows that there is no longer a use for any relationship between data entries, then we'll be able to say that RDBMSs are obsolete. Actually both headlines (/. and the linked article) are mistaken about what Michael Stonebraker is saying. He is talking about read intensive applications mostly and he is talking about optimization of data for reading purposes. This does not mean that RDBMSs are obsolete for all uses, just that he sees a faster way to retrieve data for certain uses.
You can't handle the truth.
I can understand people not reading every link on a slashdot article they comment on. But if you post the bloody link, is it too much asked to actually RTFA?! It's an article about a column. The actual column is quite interesting.
To add some content, this is about optimal storage for SQL databases in a data warehouse context where there are some interesting products that use something more optimal than the one size fits all solutions currently available from the big RDBMS vendors. The API on top is the same (i.e. SQL and other familiar dataware house APIs), which makes it quite easy to integrate.
Regarding the obsolescence question, one size fits all will be good enough for most for some time to come. Increasingly people are more than happy with lightweight options that are even less efficient on which they slap persistence layers that reduce performance even more just because it allows them to autogenerate all the code that deals with stuffing boring data in some storage. Not having to deal with that makes it irrelevant how the database works and allows you to focus on how you work with the data rather than worrying about tables, rows and ACID properties. Autogenerating code that interacts with the database allows you to do all sorts of interesting things in the generated code and the layers underneath. For example, the hibernate (a popular persistence layer for Java) people have been integrating Apache Lucene, a popular search index product, so that you can index and search your data objects using lucene search queries rather than sql. It's a quite neat solution that adds real value (e.g. fully text searchable product catalogs are dead easy with this).
Column based storage is just an optimization and not really that critical to the applications on top. If you need it, there are some specialized products currently. The author of the column is probably right about such solutions finding their way into mainstream products really soon. At the application level, you'll still be talking good old SQL to the damn thing though.
Jilles
The relational concept will still exist regardless of the underlying storage methods.
You are being MICROattacked, from various angles, in a SOFT manner.
To be a relational database the database must meet a very specific set of requirements. While a standard view of the databases from the DB administrators and normal users view may allow limited ways to manipulate the data, looking at the actual storage structures and how to efficiently use the resultant files can provide some extremely efficient computational methods. For example, if one structures data in a relational database with few fields, perhaps as low as two, per representation where each representation represents a single file then the data read directly from the file, the reads may be via flat file techniques, into an array or efficient storage table, then you achieve the best of both worlds. If the above example requires compressed data, then the relational data must be read from a single file via DB operations with two different mappings overlaying the single database file. The programmer must understand the data orientation so that compression/decompression occurs correctly. Extremely fast reads/writes may be achieved this way. The advantage of a column oriented database is that the files are inherently optimized for data mining without the need to hire an expensive programmer. If the company had multiple requirements for the same data then multiple databases may be required, unless they are willing to hire the expensive programmer. A key problem results when multiple databases loose synchronization. BTW, row based databases optimized for storage size (footprint) compress data by column, not by row or record. Using these techniques, I have achieved far greater data compression than comparable Google stored data.
Not Quite. Stonebraker was THE core developer on Ingres which was the second relational DB created (System R was the first developed by Codd et.al using SQL). He operated at both ends of the spectrum. Gray/Mohan did the same as well. While System R disappeared, Ingres was developed into a major company (ingres) and was ultimately bought by CA.
Later, Stonebraker's work on postgres (theorey AND code) was how to handle different datatypes within databases. He took an OO approach to that. That was directly used in Illustra and then went on to Informix. More importantly, Oracle used a lot of that work to create 8i as has other DBs. IOW, he IS a leading theorists AND knows the code.
Considering that he has been on top of all the major advances within the DB world, why would you discount what the man says? As it is, you mention Gray and Mohan who both did some good work at IBM, but have not really advanced DBs forward that much. They simply moved relational model DB forward( Bascially, they were red herrings). But Stonebraker is working across ALL the spectrums and contributes heavily to knew models. His work is everywhere.
Finally, think about what he says. The column major is more useful for data warehousing BECAUSE it allows for data to be compressed quickly, tighter (which makes sense), AND allows you to work with just the data that you need. In a row major, you will end up creating and maintaining indexes to increase the speeds of reads. But an index is for the most part a single (or just a few) columns, which basically makes them a column major. But this requires LOADS of cpu and space to maintain. The column major approach simply keeps the indexes, if you will and discards the rows. This allows for FAST operations if you are doing LOADS of reads, and little changes. That is PERFECT for data warehousing.
So armed with that knowledge, exactly WHY would you discount his work and his statements?
I prefer the "u" in honour as it seems to be missing these days.