Slashdot Mirror
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."
Okay, at the risk of sounding stupid...
Since when is a column store database and a relational database mutually exclusive concepts? I thought that both column store and row store (i.e. traditional) databases were just different means of storing data, and had nothing to do with whether a database was relational or not. I think the article misinterpreted what he said.
Also, I don't think it's news that Michael Stonebraker (a great name, by the way), co-founder and CEO of a company that (surprise!) happens to develop column store database software, thinks that column store databases are going to be the Next Big Thing. Right or wrong, his opinion can't exactly be considered unbiased...
The name of his blog is The Database Column after all.
"I'd rather be a lightning rod than a seismometer." -Ken Kesey
Relational databases aren't being obsoleted. Some schema design heuristics are.
0xfeedface
Is there a dual-mode db, that lets you create a row-based or column-based "table"? I imagine cross-mode queries would kill performance, but at least you could have a system front-loaded with row tables, where data comes in, and then archive this data over time into the column-based tables, so that reads were fast.
stuff |
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?
>"column stores will take over the [data] warehouse market over time, completely displacing row stores."
Hmmmm. So if I rotate my Paradox or Excel table by 90 degrees, I have achieved database coolness? Who knew it was so easy.
Some mornings it's hardly worth chewing through the restraints to get out of bed.
...is duping himself and thus Slashdot is duping the stories by extension.
Stonebraker has been pushing the concept of column-oriented databases for quite some time now, trying to get someone, ANYONE, to listen that it's superior. While I think he has a point, I'm not sure if he really goes far enough. Our relational databases of today are heavily based on the ISAM files of yesteryear. Far too many products threw foreign keys on top of a collection of ISAMs and called it a day. Which is why we STILL have key integrity issues to this day.
It would be nice if we could take a step back and re-engineer our databases with more modern technology in mind. e.g. Instead of passing around abstract id numbers, it would be nice if we had reference objects that abstracted programmers away from the temptation of manually managing identifiers. Data storage is another area that can be improved, with Object Databases (really just fancy relational databases with their own access methods) showing how it's possible to store something more complex than integers and varchars.
The demands on our DBMSes are only going to grow. So there's something to be said for going back and reengineering things. If column-oriented databases are the answer, my opinion is that they're only PART of the answer. Take the redesign to its logical conclusion. Let's see databases that truly store any data, and enforce the integrity of their sets.
Javascript + Nintendo DSi = DSiCade
You've all heard of the IBM product called DB2, right? So what was DB1? Answer: IMS, which is a hierarchical database. They were a pain in the ass to use--PSBs and all--but they were/are faster than hell and I doubt any company is going to throw them out for any reason. Same goes for relational databases. They're going nowhere. Sure, we have room for more but nobody is going to displace the RDBMS anytime soon.
No. There, that was easy !
It's like the packet of crisps that says "Is there a 20 pound note in here !!?" - the answer should always be 'No'.
Except maybe for one person.
sed -e 's/crisps/potato chips/' -e 's/pound/dollar/'
Obviously, he's biased. But more importantly, he just said that column-store databases are going to take over the WAREHOUSE market. That doesn't mean that row-store databases are going to become obsolete, because there will always be applications out there that do a substantial amount of writing as well as reading.
In fact, the new wave of user-generated-content websites and webapps seems to me to indicate the exact opposite - if anything, row-store databases, with their usefulness in write-heavy applications, should becoming, if anything, more and more necessary/useful on the web.
So...chalk this one up to some grandstanding on the part of a guy who wants to put more money in his pockets...
From TFA:
"Column-oriented databases -- such as the one built by Stonebraker's latest start-up, Andover, Mass.-based Vertica Systems Inc. -- store data vertically in table columns rather than in successive rows. "
Marketing hype for his startup.
What a sleezeball.
Column stores are great (better than a row store) if you're just reading tons of data, but they're much more costly than a row store if you're writing tons of data.
Therefore, pick your method depending on your needs. Are you storing massive amounts of data? Column stores are probably not for you...Your application will run better on a row store, because writing to a row store is a simple matter of adding one more record to the file, whereas writing to a column store is often a matter of writing a record to many files...Obviously more costly.
On the other hand, are you dealing with a relatively static dataset, where you have far more reads than writes? Then a row store isn't the best bet, and you should try a column store. A query on a row store has to query entire rows, which means you'll often end up hitting fields you don't give a damn about while looking for the specific fields you want to return. With column stores, you can ignore any columns that aren't referenced in your query...Additionally, your data is homogenous in a column store, so you lose overhead attached to having to deal with different datatypes and can choose the best data compression by field rather than by data block.
Why do people insist that one size really does fit all?
ad logicam Claiming a proposition is false because it was presented as the conclusion of a fallacious argument.
The next big thing in DBMS:
turning your head sideways.
You can't talk about Wikipedia's flaws on Wikipedia
In my IT business, a vast majority of our top tier clients (grossing over US$100 million annually) are still using antiquated software that is still using a relational database backend. While these companies are generally VERY efficient in terms of providing services or products to their market, their accounting, purchase orders and project management software is decades outdated. Many of the companies that maintain these packages have merely made the interface more current (but still 5+ years old, but are still using terribly outdated software. I can't begin to tell you how often the words "FoxPro" and "MS SQL" come up and it ends up being a relational database "solution" or even worse.
It is very frustrating because we do have programmers on staff that create third party plug-ins to these databases to try to make solutions that the OEM code doesn't. When you meet younger programmers, many of them are frustrated themselves to work on ancient solutions that have no hope of being upgraded, because these industries we work in are not in a rush to try anything new and shiny, but instead are happy with the status quo.
I just bid a job a few months back that would cost $150,000 to upgrade their database infrastructure, and likely save the company $300,000+ annually in added efficiency, less downtime, and a more robust report system. Guess what they said? "We all think it is fine the way it is." That's money thrown out the window, employees who are frustrated (without knowing why), and forcing the company to lose efficiency by not being able to compete with newer companies that are utilizing newer technology to better their bottom line.
Ugh.
I tried turning my Oracle server on its side to get column-store access. Strangely, I didn't see any increase in performance. Perhaps I'll try the other side...
It must have been something you assimilated. . . .
Are they now officially an also-ran? Has the whole concept failed to be usefully implemented commercially, or will it be another Lisp--elegant, beautiful, and largely unused because it's kind of weird?
Anyone who loves or hates any language, platform, or manufacturer, doesn't know what they're talking about.
For data warehousing, a higher or different level of abstraction may be useful and make database design easier, particularly as paralellism becomes more and more common. Storing rich markup language or media in a database might be problematic as well.
But there's no way that RDBMS's are going away -- relational algebra simply solves too many data storage problems.
Conformity is the jailer of freedom and enemy of growth. -JFK
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.
sed -e 's/crisps/potato chips/' -e 's/pound/dollar/' -e 's/note/bill/' -e 's/packet/bag/'
Not A Sig
Along with Procedural Programming, this could REVOLUTIONIZE the software industry!!
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
Maybe his approach is all wrong. The database my company uses has MANY tables that are rarely written to, but a few that are written to ALL the time. Instead of trying to cram his 'one size fits all' database scheme down our throats and replace the current 'one size fits all' database scheme, maybe he should be trying to create a database engine that can do both.
I think you would have to determine the main use of the table beforehand (write-seldom or write-often), but the DB engine could use a different scheme for each table that way. I know some will claim that it can't be more efficient to split things this way, but remember that this guy is claiming 50x the speed for write-seldom operations.
As for Relational Databases... How is this exclusive to that? This is simply how the data is stored and accessed. If he is claiming 50x speed-up because he doesn't deal with the relational stuff, that's bunk. You could write a row-store database with much greater speed as well, given those parameters.
"If you make people think they're thinking, they'll love you; But if you really make them think, they'll hate you." - DM
'"In every major application area I can think of, it is possible to build a SQL DBMS engine with vertical market-specific internals that outperforms the 'one size fits all' engines by a factor of 50 or so," he wrote.'
I know very little about DBMS systems, but I thought it has always been true that you can achieve monumental performance increases by building somewhat specialized database systems in which the internals of the system make assumptions, and are tied to, the structure of the data being modelled. In fact, when RDBMS systems came in, one of the knocks on them was that they were far more resource-intensive than the hierarchical databases they displaced. However, the carved-in-stone assumptions of those models made them difficult and expensive change or repurposed.
I'm sure I remember innumerable articles insisting that "relational databases don't need to be really all that much terribly slower if you know how to optimize this that and the other thing..."
In other words, as an outsider viewing from a distance, I've assumed that the increasing use of RDBMS was an indication that in the real world it turned out that it was better to be slow, flexible, and general, than fast, rigid, and specialized.
So, what is a "column store?" It sounds like it is an agile, rapid development methodology for generating fast, rigid, specialized databases?
"How to Do Nothing," kids activities, back in print!
Traditionally perl-objects are hashes with one blessed hash per instance. The hash contains all the instance variable values using their names as keys.
instead one can use blessed scalars holding a single integer value for instances and let the class variable contain all the instance data in arrays indexed by the instances scalar value.
This technique was originally promoted as an indirection to protect object data from direct manipution that bypassed get/set methods. But it also allows the object to be either row or column oriented internally. that is the class could store all the instance hashes in an array indexed by the scalar. or it could store each instance variable in a separate array that is indexed by the scalar value.
Thus the perl class can, on-the-fly, switch itself from column-oriented to row-oriented as needed while maintaining the same external interface.
Of course this is not a perl-exclusive feature and it can implemented in other languages. It just happens to be particularly easy and natural to do in perl.
Some drink at the fountain of knowledge. Others just gargle.
The near future. Mr. Stonebraker walks into a store.
Mr. Stonebraker: How much are these plums?
Checkout girl: Plums? They're $0.99, $1.39, $12.49, $15.99, $26.38, $13.37...
-Rob
Biblical fiscal responsibility
The relational concept will still exist regardless of the underlying storage methods.
You are being MICROattacked, from various angles, in a SOFT manner.
On the contrary.
... etc
From a standard 3rd generation programing language one can read and write into flat files and we can do close to this with a hierachical database.
We lose this with relational databases because the way the database organises data has no direct mapping to the way it might be set up in a standard programming language.
What this means is that every transaction to and from the database must go through a literally horrible re-mapping. IE. The language data structures do not correspond to the RDBMS data structures and visa versa.
As an example - in postgreSQL the last I looked at writing a simple row into a table where there were something like 100 columns in the row...
In the 3rd generation programming languages this was just a simple structure with 100 entries.
The data transfer from that structure generated a function call with more than 1000 parameters. This was to be mapped and re-mapped with each call to transfer data, this is even though the structure itself is static and determined at compile time.
Next: There were about 10 parameters per field (column).
1: Column name
2: Column name length
3: data type
4: data length
5: character representation
finally 10: Address where the data lives.
The thing is such a table could be set up very easily and populated with a simple loop that rolls in the required values via say a mapping function with about 10 arguments. This could be done ONCE at run time to prepare for the transfer of data and then the same table could be referenced for each call and simply an address could be sent with the transfer.
Noooo.. It was dynamic and the data was encoded as parameters on the stack. This means the stack must be build and torn down and rebuilt for each call.
Next - the implementation was so bad that the program would run in test mode with only a few parameter but it failed when the whole row was to be transfered.
I gave up on that interface.
---------------
Oracle had pre-compilers. They did the same damn thing. The code generated by the pre-compilers was just awful.
---------------
While there is much good to say about RDBMS's in general. The issue I ran into was the interface from 3rd generation languages took a HUGE step backward. IMHO we should have a high level language statement called DBRead() and DBWrite(). In C this should generally correspond to fread() and fwrite(). If this is too complex then DBWriteStruct() could be implemented with suitable mapping helper function.
Nooo...
In the old days one could read and write into a flat file at a given location with a single statement or function call depending on the language. Of course "where" to read and write became a real issue and I do fully understand the complexity of file based tree structures and so forth, especially since I wrote a lot of code to implement these algorithms.
The thing is now we have RDBMS and other solutions that give us the data organisational abilities we need - and we lose the ease of mapping these structures into a suitable structure or object in the programming language.
I for one do not think we have stepped forward very far at all.
-------------
I'll toss in a case in point made by a good buddy of mine who just happens to be one of the top geophysical programmers in this city.
One of his clients was running an application hooked to an Oracle database running on a fast SUN. Run times were measured in close to a day.
Finally they removed the Oracle interface and replaced it with a glorified flat file. They clearly built in some indexing. The result is the run times dropped to under 20 minuets.
As my buddy says - He will NOT use any RDBMS. He can take 5 views of the data comprising 1000's of seismic lines and the user can click on any trace number, line number, well tie and so forth and in real time he can modify all views of the data on as many as 5 s
Here's how I write out a customer record:
$dbh->do(
'insert into customer (id,name,yada1,yada2,yada3) values (?,?,?,?,?)',
undef,
@customer{id,name,yada1,yada2,yada3}
);
I think that's even easier than your 3rd-gen code, and I didn't have to write my own indexing code.
Living in Kentucky, I can tell you a relational database would be handy if actually used. Why I've got in-laws that, well, I won't go into details. Let's just say I suspect my wife married an out of stater for fresh genes.
What? Not that kind of relational?
The world is made by those who show up for the job.
- He helped created THE first relational DB.
- He later moved to creating an Object-Oriented Relational DB with Postgres in the 80's. Much of that tech has found its way into other DBs such as Oracle and even helped create the OODBMS world.
- Now, he is creating the Column store DB and announces that this will be the next big thing.
I would listen to him. Biased or not, He has a better track record than most intelligent ppl (and all the wanna-be/hasbeens; dvrack comes to mind) in the tech field.I prefer the "u" in honour as it seems to be missing these days.
#1: Assuming what you think your customer needs is what your customer wants.
#2: Assuming they are the ones who made the mistake when you lost the job.
On the contrary.
From a standard 3rd generation programing language one can read and write into flat files and we can do close to this with a hierachical database.
I think there is a key distinction here. Application object store vs data management. Hierarchical db's are far better at storing object information, but *far* worse at real data managment.
We lose this with relational databases because the way the database organises data has no direct mapping to the way it might be set up in a standard programming language.
What this means is that every transaction to and from the database must go through a literally horrible re-mapping. IE. The language data structures do not correspond to the RDBMS data structures and visa versa.
In LedgerSMB, we solved this by putting a functional interface in the db. Then we dynamically map the objects and their properties into functions and arguments. Works great :-)
As an example - in postgreSQL the last I looked at writing a simple row into a table where there were something like 100 columns in the row...
You are either trolling or you need to fire the DB architect who designed that. THere is *no way* that a 100-column table is good DB design. (Ok, mathematically, there is nothing that precludes it being good db design, but I can't even imagine a scenario where this would be OK).
In the 3rd generation programming languages this was just a simple structure with 100 entries.
Oh, you were the one who designed the 100-column table. Sorry..... Please go out and get some books on db design. You will thank me :-)
The data transfer from that structure generated a function call with more than 1000 parameters. This was to be mapped and re-mapped with each call to transfer data, this is even though the structure itself is static and determined at compile time.
IMO, your problem honestly is in the fact that you are using a monkey wrench as a ball peen hammer. It may sorta work but you are using the wrong tool for the job. If you want a simple object store use BDB or something like it. If you want a real data management solution, build your db *first.* If that is not your goal, use something other than an RDBMS.
Next: There were about 10 parameters per field (column).
... etc
1: Column name
2: Column name length
3: data type
4: data length
5: character representation
finally 10: Address where the data lives.
The thing is such a table could be set up very easily and populated with a simple loop that rolls in the required values via say a mapping function with about 10 arguments. This could be done ONCE at run time to prepare for the transfer of data and then the same table could be referenced for each call and simply an address could be sent with the transfer.
Noooo.. It was dynamic and the data was encoded as parameters on the stack. This means the stack must be build and torn down and rebuilt for each call.
How is this an issue with RDBMS's?
Next - the implementation was so bad that the program would run in test mode with only a few parameter but it failed when the whole row was to be transfered.
Again, this is not a PostgreSQL problem ;-)
I gave up on that interface.
From your description, that sounds like a wise choice.
While there is much good to say about RDBMS's in general. The issue I ran into was the interface from 3rd generation languages took a HUGE step backward. IMHO we should have a high level language statement called DBRead() and DBWrite(). In C this should generally correspond to fread() and fwrite(). If this is too complex then DBWriteStruct() could be implemented with suitable mapping helper function.
Again, this is an issue with the frameworks you are using. Personally, I tend to do the
LedgerSMB: Open source Accounting/ERP
I think the object database management system (ODBMS) will overtake RDBMSs in the future for several reasons (from the link and my own musings):
.NET, C++ and Smalltalk. This makes implimentation quick and easy - yet stable and scalable at the same time.
1. Object-oriented databases are designed to work well with object-oriented programming languages such as Python, Java, C#, Visual Basic
2. ODBMSs use exactly the same model as object-oriented programming languages.
3. It is also worth noting that object databases hold the record for the World's largest database (over 1000 Terabytes at Stanford Linear Accelerator Center).
4. Access to data can be faster because joins are often not needed (as in a tabular implementation of a relational database). This is because an object can be retrieved directly without a search, by following pointers (e.g. the objects are stored in trees for fast retrieval). Dynamic indexing schemes further speeds up retrieval of full text searches.
5. Provides data persistence to applications that are not necessarily 'always on' - e.g. HTTP based stateless applications.
I think RDBMSs will be around for some time -- but they will be relegated to more structured situations and smaller data sets. ODBMSs will take over where data is changing, persistence is critical, data types are mostly large binary objects with associated meta-data, and datasets are humongous.
Right now my favorite ODBMS is the ZODB (Zope Object Data Base) - an ODBMS system tightly integrated with both Python (implimented using Python's native 'pickle' object persistence functionality), and the Zope web application development system - which itself is built with and uses Python. You can learn more about Zope at Zope.org.
Lodragan Draoidh
The more you explain it, the more I don't understand it. - Mark Twain
The next geekSessions is on this topic. If you're interested in hearing about alternatives to RDBMS in and using them in practice, take a look at the site. The event will be held on October 2nd in downtown SF and will also be available via webcast. In addition to the presentations, we'll have a Q&A session along with some food and FREE BEER. Speakers at the event are:
Josh Berkus from the PostgreSQL core team
Paul Querna from Apache and Bloglines (wrote his own filesystem for Bloglines)
Chad Walters from Powerset who is implementing BigTable there.
Hope to see you there!
That's why row-oriented databases have indexes and perform index scans.
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.
Michael Stonebraker is certainly a well respected nae and he was been right on these issues in the past. Coinsidently I'd testing my software with a new version of PostgreSQL as I type. I think colum vs. row storage can be considered simply a option. I can even see it being an option that you specify at the table level. Most DBMS users really don't have much data. Today a 1,000,000 row table can be cached in RAM on even a low-end PC based server. Once cached in RAM row vs. column storage does not matter. I would imagine that 99& of the database table in te world have far fewer then a million rows. This discussion applies only to the very few that are really large.
Will the imminent transition to SSDs make any difference? Because row-based DBs means you're typically reading large chunks (one raw) sequentially, while columns stores means you're reading many small (number of columns) chunks for every row. I'd think that if random access time was almost none, you'd get almost the same write performance while read performance could be greatly improved because you only read the columns you need. It'd certainly make DB design easier too if you didn't have to worry about putting very light information in the same table as heavy blobs.
Live today, because you never know what tomorrow brings
You are confusing an RDBMS with a persistent storage mechanism. It's really not hard to just keep data persistent any more. You don't need a 3GL or anything fancy, just some hooks to record your modifications on permanent storage, and keep a small working set cached in memory. It's an easy, trivial, solved problem. And it was solved before relational databases were invented.
RDBMSs do a lot more. Here are just a few advantages:
* different applications can access the same data
* guarantee integrity via declarative constraints that can validate against all of the data at once, not just the single record in question
* different applications can have the same guarantees of integrity, and a bug in the first application can't break the guarantee for the second application
RDBMSs were invented for a reason. Many, many software bugs can be traced back to a bad data state -- some invariant that was broken and uncaught. Often, these bugs are not caught until long after the insert has taken place, and often cause a cascade of new bad data and you don't find out until many records are wrong. A lot of code is imperative, and re-stating the invariant declaratively (i.e. a database constraint) helps catch a lot of those bugs.
Trying to put these declarative constraints in the application is a bad idea. When should they be checked? And in which applications should they be checked (all of them, one would hope)? If you see a declarative constraint, are you sure it's correct, or might it have been added after inconsistent data was entered and before the constraint was actually run?
Databases solve this by making some promises. If you put a ".. CHECK (age > 0)" on an attribute, it will check all the records before applying it, and then all the records afterward will need to pass through that constraint. That's a lot better of a guarantee, and you know it's true for all applications. Someone else's bug or quick hack won't violate it, so your application can rely on that as the truth. Same with UNIQUE or FOREIGN KEY.
If you think about your reasoning for a moment, it's very narrowly focused on storing and retrieving single records. Presumably, anything needing to look at the data as a whole would need to read it fully into the application and process it from application code.
You don't take into account other readers of data who might require consistent reports or anything else that needs to look at more than one record. You also don't take into account the horrible mess you have when the application is wrong and stores bad data, or when you need to do data format changes. In the types of databases you describe, almost any change requires reorganizing the data physically. In an RDBMS, you can make many changes without physically changing the physical layout.
Social scientists are inspired by theories; scientists are humbled by facts.
I don't think that has anything to do with the article. That is about storage on disk, not about manipulating pointers in memory to such an extent that a programming language that should never have been invented in the first place becomes even more ununderstandable.
Ouch. And this exactly why SQL should die as the primary interface to the RDMBS. How the hell is my compiler going to help me find simple typing errors when the interface to use the RDBMS is built upon ... strings! You are generating code from code, that's not integration, that's a hack! It's useful, as there is no sound other way to approach an rdbms, but it's not a pretty sight.