#200 50 Years of SQL with Don Chamberlin, Computer Scientist and Co-Inventor of SQL

Hi, I'm Maggie, VP of Curriculum at datacamp. And I know firsthand how overwhelming it can be to keep up with the rapid changes in data and AI. But staying ahead doesn't have to be hard. That's why our curriculum team has curated the best learning content to help you and your team stay ahead, covering everything from data and AI literacy for busy executives to cutting edge generative AI for developers, and everything in between. Whether you're upskilling yourself or your team, we make learning practical, engaging and flexible. It just works. Power your data and AI transformation journey on datacamp.com.

The database revolution has just been unfolding rapidly over the last half century, and I was really privileged to take a part in it. SQL didn't cause this revolution. It was caused by economics.

Welcome to Data Framed. This is Richie. We're celebrating two anniversaries today. First of all, it's episode 200 of Data Framed. Thank you for listening. I'm really proud to be your host and I hope I've helped you learn some useful things about data and AI. Secondly, it's 50 years since Don Chamberlain and Ray Boyce published the first ever paper on the SQL programming language. I'm sure I don't need to tell you that this changed the world. Even now, every data practitioner needs some SQL skills because that's how we access our data. We only bring you the best on this show. And today's guest is Don Chamberlain himself. He's here to talk about the early years of SQL, how the language went from an idea about easier ways by accessing data to world domination. We spend a lot of time on the show thinking about the future, but I think it's also important to occasionally step backwards and appreciate how far we've come. Lets hear Don's story. Hi Don. Welcome to the show.

Hi Richie. Thank you. Pleasure to be here.

I'd love to start by just finding out how you first became interested in databases.

Well, I'll start from the beginning. In 1970, I was finishing my graduate studies at Stanford and I took my first professional job with IBM at the Watson Research center in Yorktown Heights, New York. I moved from California to New York in the winter, which was not a move I recommend if you enjoy warm weather. A few months later, my friend Ray Boyce also completed his graduate work at Purdue and he joined IBM at the same location where I was. Well, Yorktown was the central research facility of IBM. And the mission of IBM Research is to study technologies that might influence IBM's future products. And in 1970, there was kind of a revolution going on. The cost of computing was coming down very quickly, and lots of companies were putting data online for the first time. And this seemed like a business opportunity. So the group that Ray and I were in was assigned to study the state of the art in database management with an eye to influencing IBM's future products.

Okay, and what was this first database that you got interested in?

Well, we studied something called the DBTG report. So let me tell you where that came from and why we were interested in it. In the early 1970s, the most respected person in the database industry was a guy named Charles Bachmann of General Electric, known to his friends as Charlie. And Charlie had actually invented the concept of a database management system. He was the first one to call for a separate software layer to manage data that was shared by multiple applications. And this was a pretty important concept. And for inventing the database management system, basically, Charlie received the ACM Turing Award, which is the most prestigious award in computer science. Well, Charlie had actually built a database management system that was called ids, stood for Integrated Data Store. And IDS stored information in the form of records and connections between records. You could think of them as pointers. In ids, a program could navigate through what Charlie called data space, moving from one record to another by following these pointers to find an answer to a question. And in fact, when Charlie gave his Turing Award lecture, he titled it the Programmer as Navigator. Well, one of the most popular business programming languages at the time was cobol. And there was a movement to add database management functions to cobol. And a committee was formed for this purpose called the Database Task group, was abbreviated DBTG. Charlie was a member of DBTG, and the group published a report in 1971 defining a set of commands for navigating in data space based on Charlie's ideas. Well, the DBTG report was pretty important at the time Ray and I spent some time studying was wonderfully complicated. It had currency indicators, set of current selection rules. It had a fine command with seven different versions. It could do a pretty good job of answering questions that were anticipated in the database design. But for unanticipated questions, sometimes you were out of luck. Ray and I wrote a review of the DBTG report, and we suggested some incremental improvements. We thought if we could manage to understand something as complicated as dbtg, our careers would be off to a good start. That's funny.

I love the analogy there of working with data as being navigating. I think a phrase is not often used but you do spend so much time trying to work out how different bits of data are connected together. And it sounds like this idea of data being connected is leading towards the idea of relationships between data and relational databases. So can you talk me through how relational databases came about and how you got interested in them?

Well, sure. All this came about because of a paper written by Ted Kopp. Ted was a scientist at IBM's research laboratory in San Jose, California. And in June of 1970 he published what became a very famous paper called A Relational Model of Data for Large Shared Data Banks. The basic point of Ted's paper was that Charlie Bachman had gotten it all wrong and that navigating through data space was a bad idea. Ted thought that database queries should not look like programs that tell the computer what to do. He wanted to express queries in a high level non procedural language. He liked to say, tell me what you want, not how to find it. Well, I read Ted's paper as part of my learning process in getting up to speed on the state of the art in databases. And on first reading I wasn't much impressed with this paper. Ted was basically a mathematician and his paper contained a lot of mathematical jargon. It defined a relation as a subset of the Cartesian product of a set of domains. And it introduced concepts like data independence and normalization and operators like permutation and projection and join. And my impression of all this was that Crud's paper was interesting from a theoretical point of view, but I couldn't see that it was really grounded in practical engineering. But I kept on hearing more about this relational data model. I heard about a symposium that was going to be held in Miami beach in December of 1972, and it was going to feature a tutorial on relational databases. Well, traveling to Miami in the winter had a certain appeal. So I got permission to attend this symposium. It was called the Coins 72 Symposium Conference on Information Systems. And I actually met Ted Cod for the first time on the beach at Fountain Blue Hotel. I attended this tutorial which was taught by Chris Dase, and I have to describe it as a conversion experience. For the first time I began to understand the simplicity and power and elegance of ted's relational approach. Queries that took a whole page in code in DBTG could often be expressed in a single line in a relational approach. So when I returned to New York, I wasn't interested in DBTG anymore. I was taking up a new interest in relational query languages.

That's fascinating and I love that, even though it was a hugely influential paper. Your first reaction to Ted Scott's work was like, oh, this is mathematical nonsense. All theoretical, no practical applications. But once you sort of see it in action, it is actually incredibly powerful. So I love how it just translates into something more practical and more real. I think the first sort of real implementation of this was the System R project that you worked on, is that right?

Well, there were actually several things going on more or less at the same time in different places in IBM and also at other different companies. There was the Ingress project, for example, at Berkeley. But I'm going to talk mainly about SYSTEMR because that was the project that I was associated with. There were a lot of people who saw the power and simplicity of cod's approach, but the whole idea depended on a high level query language with an optimizing compiler that could turn it into efficient code. And the question was, that sounds like a good idea, but was it just science fiction or was it really ready for prime time? And in 1973, IBM decided to answer this question by building an industrial strength relational system just to prove it could be done. And this was done at IBM Research. They created a project for this purpose and called it System R. Well, SYSTEMR was located in San Jose because that's where Ted Cod was. And There were about 14 people, including Ray and myself, who were gathered from several IBM sites all over the country to come together and work on this System R project. Well, I wasn't very happy about moving to New York at that time. I'm sorry about moving from New York to San Jose. At that time. I had just bought a house and my wife had a good job teaching high school. I felt disrupted. But I made the move and I went to San Jose to join the SYSTEMR project. And that turned out to be the best decision I ever made. Working on IBM's first relational database system. Really turned out to be the opportunity of a lifetime.

It's interesting how these cross country moves have been problematic each time.

But yeah, I'm used to Stanford, I've been moved. That's the legend.

And then from System R, it seems like this is leaning towards the really important paper that you wrote around the SQL programming language. So where did that idea come from?

Well, to tell you the truth, Ray and I liked some parts of crud's ideas better than others. We really liked this idea of a non procedural query with the slogan tell me what you want, not how to find it. What we didn't like was the mathematical jargon in ted's papers. We wanted to design a language for a new class of user. We called them casual users. We thought a casual user is a professional who needs access to data, but he doesn't want to be a computer programmer, and he doesn't even want to rely on a computer programmer. He might be an urban planner or a financial analyst or an insurance company executive. He might have questions that vary from day to day, and he might want his results pretty quickly. Well, the database Systems of the 1970s just didn't meet these requirements. So to serve this casual user, Ray and I wanted to design a new language. And we set certain goals for it. Number one, we wanted to use the term tables instead of relations. Everybody knows what a table is. Number two, we wanted to base the language on ordinary English words like select and goal. Number three, the language should have no special symbols and it should be easy to type on a keyboard. And goal number four, which is maybe the most challenging one, we wanted it to have something that we called the walk up and read property, meaning in simple cases, a user with no special training should be able to understand a query just by reading it. Well, those were the goals that we set for ourselves. And we, we called this new language SQL, which was an acronym for a structured English query language.

It's amazing how the things you were worrying about back then 50 years ago are things that we're still worrying about now. So, for example, there's a big push at the moment to make data more accessible to everyone, regardless of whether you have a technical background or not. And I find it fascinating that this is something you worried about when you were first designing the SQL language, that people who didn't have this strong mathematical background could still make use of the technical technology. So you mentioned the idea of walk up and read. So people just walk up, look at the code, and it makes sense to them. It sounds like a difficult thing to measure. How do you know if you've been successful at that?

That's a good question. It's a hard thing to do and it's a hard thing to measure. And I'll never know really how successful we were, but we had a psychologist on the staff named Phyllis Reestner. And Phyllis conducted an experiment at San Jose State University teaching SQL to college students who'd had no programming experience at all and recording their progress and the kinds of errors that they made. It turned out that these college students could become proficient in SQL after a few hours of instruction. Their most common error was something funny. They would forget to put quotes around strings, for example, if a Query contained the phrase name equals fred. You had to put quotes around fred to indicate that it's a constant string, somebody's name rather than the name of a column. Well, that's an important distinction, but a lot of students never understood it and intended not to put quotes around anything.

I can confirm that that is still a problem in every programming language 50 years later, forgetting to quote your strings and putting business syntax in the wrong place. So after you've sort of designed this language, I think it was initially used just within IBM. How did it travel outside that organization?

Well, Ray and I published the first SQL paper at a conference called SIGFADET in Ann Arbor, Michigan in June of 1974. SigFadet has since changed its name to SigMod, the special interest Group on Management of Data. And it's now probably the most prestigious annual database conference. This conference in 1974 was very interesting because it featured a panel discussion between Ted Cod and Charlie Bachmann. This was called a panel discussion, but everybody knew it was a debate. And in my view, Ted Cod was the winner of this debate. I think after this conference in 1974, Ted's relational approach was considered to be the new mainstream in database management. So that's why I consider that this year, 1974, starts the clock on what I've called 50 years of relational databases. And since the first SQL paper appeared in this conference, it also starts the clock on 50 years of SQL.

I have a question for you on this, because in this paper on SQL, it's spelled S E Q U E L now been shortened. Even today, there's a lot of confusion about, do I call it SQL? Do I call it SQL? I'd really love to have an official answer on this. Which do you prefer?

Well, at some point after publishing our paper, we got a letter from somebody's lawyer that said we couldn't use the name SQL anymore. It was somebody's registered trademark. So we had to officially shorten the name to SQL, which stood for Structured Query Language. So the official name of the language is now SQL. But SQL is a lot easier to say than SQL, so I usually just pronounce the name SQL and hope I won't get in any trouble for doing that.

All right, we have an official answer there. That's pretty.

I like that.

Both ways are possible. One's better for writing and one's better for speaking. So you were talking about the SQL paper. Can you tell me what happened once the paper was published?

Actually, the next thing that happened was the tragedy that SQL Paper was the last thing that Ray Boyce and I did together. Less than a month after the SIGFREDET conference, my friend Ray died suddenly and unexpectedly of a brain aneurysm.

That's a very sad event. And even 50 years later, it feels like a real tragedy. So I'm sure it must have been a shock to you. Could you maybe tell me a bit about what it was like working with Ray?

Yeah. Ray was my best friend. We moved from New York to California together. We lived near each other. We carpooled to work. I drove Ray to work at IBM on the day he had his aneurysm attack and he was taken away in an ambulance. Ray and I used to play something we called the query game. We were experimenting with different query language designs. We take turns dreaming up queries and challenging each other to express them. We explored a lot of ideas in those days, and at the end of the day, we couldn't remember which one of us was responsible for any given idea. Collaborating with Ray was the best part of my job.

That's wonderful that you have fond memories of working with him. And again, yeah, I'm sorry that such a tragedy happened to him and to your friend. I'm wondering. So after you'd had this sort of revolutionary paper, things are starting to get popular or. Who were the first people that took on this idea? Who was using SQL to begin with?

Well, you have to remember that Systemr was a research prototype. It was not an IBM product. So you couldn't just go somewhere and buy it as a research group. We wanted to gain some visibility inside IBM. To do that, we needed to have some users. So we distributed Systemr to about a dozen internal IBM sites and also on a joint study basis, to three frontline IBM customers. So that was Boeing and Pratt Whitney and Upjohn. And we had quarterly meetings with all of our users to learn about their experiences and respond to their suggestions. It was during this period that we had to shorten the. The name to SQL.

Okay, so it was a lawsuit that intervened there. Those darn lawyers. Oh, all right. So to begin with, it was a research project. And then when was SQL first commercialized?

Well, since SQL was invented at IBM Research, you might expect that IBM would be the first to bring it to market, but that's not actually the way it turned out. Interestingly enough, IBM in those days had another database product called ims, and they weren't in a hurry to introduce a competitor to their successful product. But they did allow the System R group to publish their results in the open technical literature. That was generous. And that's how we published the SQL paper and lots of other papers about the details of the system R work. Well, there was a small startup company called Relational Software Incorporated, abbreviated rsi, that took an interest in these papers. The founders of RSI guessed correctly that IBM would eventually release a SQL product on mainframe computers. And they saw an opportunity there. They decided to build a product that was compatible with SQL on less expensive hardware platforms and to bring it to the market quickly. And they executed this plan very successfully. In fact, in 1979 they released a SQL product called Oracle running on a mini computer, a PDP 11. And this product was immediately successful, so much so that RSI changed its name to the Oracle company. And Oracle was actually the first commercial implementation of SQL.

That's fascinating because I've not heard of rsi, but obviously Oracle is a huge brand name. So I realized about the name change.

IBM itself didn't release a SQL product until 1981 on some of its smaller computers. That was two years after Oracle and their strategic mainframe product called DB2 came out in 1983. That was four years after Oracle. And by this time, well, Oracle had pretty much established a commanding lead in the database market.

So it seems like that was the main competition then was between Oracle and IBM in the early days. Were there any other players?

Yeah, there were. I've been talking about Systemr, a research project to prove the concept of a commercial relational system. But there was another project very much like that also going on at the same time at UC Berkeley. Their project was called Ingress, and it was led by two professors, Mike Stonebraker and Gene Wong. Well, Ingress had its own high level query language called Quell. And much like Systemr, Ingress was distributed for free to experimental users, which are mainly universities, and it became widely used as a teaching tool at universities. And Ingress spun off a commercial company also called Ingress in 1980. And in the early 1980s, Ingress and Oracle were the market leaders in relational databases that ran neck and neck. They both ran on VEX computers and Ingress implemented the Quell language and Oracle implemented SQL. And the Quell language was well liked by its users. But I think I'd give the edge to the Oracle marketing divisions. They marketed their SQL product very aggressively. And in 1984, Ingress decided that they had to begin supporting SQL in order to compete with Oracle.

Okay, so I didn't realize that there were all these sort of alternate languages then for accessing relational databases, but it seems within a few years things have been become standardized because you had the advent of standard for the SQL language. Can you tell me how that came about and what your involvement was in this?

I think that's an interesting story. The American National Standards Institute, ANSI created a committee in the late 1970s to define a standard database language. They kept changing the name of this committee, but usually had H2 in its name somewhere. So I'm going to call it the H2 computer. Well, at first this standard was supposed to be based on DBTG. But in 1982 they decided to extend the mission to define a relational standard. Also they wound up with two different standards, one based on DBTG and also a relational one. And when they got into the relational business, the two companies that were in the marketplace for relational systems were Oracle and Ingress, and they were both marketing SQL. And so the H2 committee decided that they would base their relational standard on some version of SQL. They went ahead and created a standard which became an ANSI standard and also an international standard with ISO. These were named database language SQL, SQL and and they were released in 1986. So that was going on in ANSI and ISO, which were voluntary associations of commercial entities, companies. But actually the standards work that had the most impact in my opinion was something that was going on somewhere else. It was at the National Institute of Standards and Technology, nist, sometimes pronounced nist. And unlike ansi, NIST is actually a branch of the federal government. And in 1992 NIST created something called a Federal Information Processing Standard. This One was called FIPS 127 that happened to be identical to the ANSI SQL standard. And even more important, they provided a test suite and a validation service for conformance to this standard. And companies whose database product passed the validation test received a license to sell their products to the federal government. Well, several companies did this and this gave a big boost to the commercial presence of the SQL language because you could sell it to the government. Well, the SQL standard has evolved a lot over the last 50 years. It started out pretty simple and it just keep growing. A lot of new features have been added. Date and time, data types, outer joins, recursive queries, the list goes on and on. A new revision has come out about every five years. The latest one came out in 2023. I think the standardization product has had several good effects on the industry. Number one, it gave customers confidence that they had multiple sources where they could buy their database software. Number two, it gave vendors a way to evolve their products while maintaining compatibility with each other. And number three, it brought some really smart people together to evaluate requirements and make proposals. This H2 SQL Standards Committee has been meeting on a regular basis for a long time now, many years.

I love that the fact that the language became standardized helped increase adoption because it gives people trust that this is an official thing and that you know what you're getting. So that seemed like a pretty important milestone. I'm wondering, are there any other important milestones in the early history of SQL that you think are important?

Sure. Before we leave the standards subject, I want to give a disclaimer here. During the decade of the 80s, when a lot of this standards work was being done, I actually took a leave from the database world and got involved in desktop publishing. That seemed to me to be the exciting thing that was happening in the 1980s. But IBM finally decided not to go into that business. So I returned to the database world around 1990. But by that time a lot of the standards work had already been done. So the credit for that belongs to other people. Well, during the 1980s, the revolution in data management really hit full stride. The cost of computing and storage kept on coming down. The volume of data generated by businesses just expanded enormously. Almost every business system, almost every business needed to acquire a system to manage their data. Oracle of course, continued to prosper. But lots of other new relational products entered the market. There was DB2 and Informix and Sybase and Tandem and Microsoft SQL Server. They all offered implementations of the SQL language. Seemed to be ruining the market for everybody. In fact, so many products were claiming to be relational that in 1985 Ted Cod published a series of 12 rules that define an authentication relational database. And you can find these rules in Wikipedia, just search for trans12rules. But starting in the 1990s there were some truly game changing developments. Three very high quality open source SQL implementations became available. Their names were MySQL and PostgreSQL and SQLite. And all three of these were fully featured, reliable high performance systems with large user communities. They all had free versions and also they had additional services that you could buy for a fee. Well, web based applications were proliferating in the 1990s. That was the dot com days. And many of these apps used one of these open source systems for data management. SQLite in particular is interesting because it's embedded invisibly all over the place. It's in most smartphones and browsers and many popular applications. So these three open source SQL systems are now among the most widely used database systems in the world.

Absolutely. They are incredibly popular, all three of them. And these are things that we still teach now on datacamp. If you want to learn to use databases, you use postcodes, I want meter the ones. So yeah, it's had a huge impact and actually even at 50 years old, SQL is still one of the most popular programming languages. So on things like the TIOBE index, their IEE Spectrum Index, like most popular programming languages, SQL is just, it's always in the top 10. So I'm wondering, how do you account for its longevity?

I can think of several reasons for that. The first and most important reason is Ted Khan got it right. The relational model is simple and powerful and flexible and elegant and really that made everything else possible. But second, I think it helped a lot that the early research by both SYSTEMR and the Ingress project at CAL were published openly. So there were basically no impediments to commercialization of this technology. That research was given away for free. Third, I think the ANSI standard provided a well defined language specification and a way for the language to evolve to meet new requirements. And that kept it alive and well as new requirements came along over a period of decades. And fourth, and this is really very important, are those high quality open source SQL implementations available for free? Well, what's not to like about that?

Free stuff is always good for sure. Excellent. So looking back on this, do you think that SQL has lived up to what you and Ray envisaged for it back in 1974?

Well, that's a good question. In some ways, SQL has been more successful than we ever dreamed it could be. But I'd have to say that the language met the goals that we had defined for ourselves. Only in part. Remember, Ray and I thought we would that SQL would be used by what we call casual users who were not computer programmers. Well, it turned out we were wrong about that. The actual users of SQL turned out to be mostly programmers building database applications. Well, I think SQL has made the work of these programmers easier and more productive. So that's a good thing. The casual users, I think are still out there, but they're not using SQL. They're using Google and increasingly I think they're starting to use AI systems like ChatGPT.

Absolutely. That's been a huge change in the last year. It's just people can have their SQL code written for them quite easily and so it's made it even more accessible. So yeah, maybe that'll bring SQL to even more people. All right, is there anything in the world of databases that you are currently excited about.

I'm retired now, but I keep hearing the term NoSQL a lot. The NoSQL movement I think is inspired by web applications that need massively scalable databases. And that's an important requirement to get this scalability. These systems usually relax one or more of the constraints of traditional relational databases. So here's some examples of that. Number one, relational databases usually have rigid schemas that say exactly what the tables look like and that are in that system. No, SQL systems sometimes relax this requirement. They might have a partial schema or maybe no schema at all. So they're more flexible. Number two, relational databases, they're limited to the relational data model. They're made out of flat homogeneous tables. In each table, all the rows look the same. Well, no, SQL systems sometimes relax that requirement and have a different data model. Now some of them are just really simple like key value stores. Others might allow tables to be nested or they might be based on some document format like XML or JSON. They're all over the place. Third, relational systems usually offer some transactional guarantees, like the well known ACID properties that keep data in a consistent state. NoSQL systems sometimes relax these guarantees a little bit. They'll often replicate data across many nodes and they might tolerate what they call eventual consistency. Meaning, well, we'll be, we'll be patient, we'll allow the nodes a little while to catch up. So is an exciting new direction. I think it's a broad name for several promising new directions in database research and that's a good thing. But sometimes I think scalability is what we want. But scalability isn't necessarily incompatible with a high level language. So I've been hearing about new language development called SQL. That's a clever name. I think SQL is a backward compatible extension of SQL that originated at UC San Diego by a professor named Yanis Peppa. Constantinople and SQL has been implemented. It's available in open source form from the Asterisk Data project at UC Irvine led by Professor Mike Carey. So you can get it in GitHub. And also there are some commercial versions of SQL coming out. They're being marketed by Couchbase and by Amazon Web Services. The Amazon version goes by a different name, Particle, but it's basically SQL. Well, SQL, it's one of those schema optional languages. And for data model it operates on collections of JSON documents which you can also view as nested tables. The correspondence between a JSON document and a nest of tables is the thing that makes SQL compatible with earlier Versions of SQL lit operated on tables. So if you're interested in this, you can get more information by just googling SQL.

That's interesting because the SQL language has been, I mean, there have been some updates, but not that many updates to it. And so having a new language that's sort of similar to SQL and backups compatible just seem like a pretty good innovation. All right, so just to wrap up, do you have any final advice for fans of SQL?

When I look back over my own career, I think of it as a case of being in the right place at the right time. The database revolution has just been unfolding rapidly over the last half century and I was really privileged to take a part in it. SQL didn't cause this revolution, it was caused by economics. Hardware was getting faster and cheaper at an exponential rate. And these advances in hardware made three things possible. The first was a clean, elegant data model like COD's relational model. And the second thing was a high level, non procedural language which turned out to be SQL. And the third thing is the optimizing compiler that brought these things together and made them commercially viable. Well, these three items, the data model, the query language and the optimizing compiler all support each other, sort of like a three legged stool. And that's what's made today's database systems possible, I think. So to wrap up in my career, I've had some lucky breaks. I've been privileged to work with some brilliant people. Ted Crud, Ray Boyce, Jim Gray, Pat Solinger, the whole system of our team. Mike Stonebraker. I'm in debt to all of these people. It's been a wild ride and I'm very grateful for the opportunities that have come my way over the years.

Wonderful. I mean, it's such a fascinating story and your achievement to just be used by so many millions of people. So it's a very impressive stuff. All right, thank you for joining me on the show, Don.

Oh, thank you, Rich. It's been a pleasure talking to you.