Back in December we ran a series of posts looking at the geographic distribution of NoSQL skills, according to the results of searching LinkedIn member profiles, culminating in a look at the relative overall popularity of the major NoSQL databases.

This week I took another look at LinkedIn to update the results for a forthcoming report, which gives us the opportunity to see how the results have changed over the past quarter:

While this provides us with an interesting opportunity to track LinkedIn profile mentions over time there isn’t a huge amount we can learn from this first update – other than that MongoDB seems to be increasing its dominance.

The only significant change that isn’t immediately obvious from looking at the chart is that Apache HBase has overtaken Apache CouchDB by a tiny margin to claim third place overall.

As we noted last time, however, Apache HBase is more reliant on the US than other NosQL databases for its LinkedIn mentions: it is the second most prevalent NoSQL database mentioned in the USA but fourth in the rest of the world.

Two other points to take into consideration:

– The results for Apache Cassandra are probably disproportionately low since we have to search for the full phrase in order to avoid including people called Cassandra.

– Previously we only searched for Membase. This time we added together the search results for both Membase and Couchbase. This may mean the result for Couch/Membase is disproportionately high since some members probably listed both.

This is not meant to be a comprehensive analysis, however, but rather a snapshot of one particular data source.

Hidden away amongst the details of our little tour around LinkedIn statistics on NoSQL and Hadoop skills was some interesting information on how many LinkedIn members list the various data management technologies in our sample in their profiles.

Our original post contained the fact that there were 9,079 LinkedIn members with “Hadoop” in their member profiles, for example, compared to 366,084 with “MySQL” in their member profiles.

Later posts showed there were 170 with “Membase” and 1,687 with “HBase”, 787 with “Apache Cassandra” and 376 with “Riak”, 6,048 with “MongoDB” and 2,152 with “Redis”, and finally, 1,844 with “CouchDB” and 268 with “Neo4j”.

This gives us an interesting perspective on the relative adoption of the various NoSQL databases:

If it wasn’t already obvious from the list above, the chart illustrates just how much more prevalent MongoDB skills are compared to the other NoSQL databases, followed by Redis, Apache CouchDB, Apache HBase and Apache Cassandra. The chart also illustrates that while HBase is the second most prevalent NoSQL skill set in the USA, it is only fourth overall given its lower prevalence in the rest of the world.

In response, a representative from a certain vendor notes “Some skills are more valued not because they are more prevalent, but because they are harder to achieve.” Make of that what you will.

Following last week’s post putting the geographic distribution of Hadoop skills, based on a search of LinkedIn members, in context, this week we will be publishing a series of posts looking in detail at the various NoSQL projects.

The posts examine the geographic spread of LinkedIn members citing a specific NoSQL database in their member profiles, as of December 1, and provides an interesting illustration of the state of adoption for each.

We’ve already taken a look at Membase and HBase, and Apache Cassandra and Riak. Part three examines the geographic spread of 10gen’s MongoDB and Redis.

The statistics showed that 41.0% of the 6,048 LinkedIn members with “MongoDB” in their member profiles are based in the US, putting MongoDB is the top half of the table for geographic spread.

Only 11.2% are in the Bay area, fewer than Hadoop, Membase, HBase, Cassandra, Riak and Redis. The results also indicate that the New York area is a hot-spot for MongoDB skills, with 6.2% – as one might expect given the location of 10gen’s HQ. Other hot-spots include Brazil (4.2%) and Ukraine (2.8%).

Redis is even more widely adopted, with only 37% of the 2,152 LinkedIn members with “Redis” in their member profiles are based in the US, although 12.0% are in the Bay area.

Ukraine is also a hot-spot for Redis skills (3.8%) as is France (3.6%) and Spain (2.9%).

The series will conclude later this week with CouchDB, and Neo4j.

N.B. The size of the boxes is in proportion to the search result (click each image for a larger version). World map image: Owen Blacker

NC State University’s Institute for Advanced Analytics recently published some interesting statistics on Apache Hadoop adoption based on a search of LinkedIn data.

The statistics graphically illustrate what a lot of people wer already pretty sure of: that the geographic distribution of Hadoop skills (and presumably therefore adoption) is heavily weighted in favour of the USA, and in particular the San Francisco Bay Area.

The statistics showed that 64% of the 9,079 LinkedIn members with “Hadoop” in their member profiles (by no means perfect but an insightful measure nonetheless) are based in the US, and that the vast majority of those are in the Bay Area.

The results are what we would expect to see given the relative level of immaturity of Apache Hadoop adoption, as well as the nature and location of the early Hadoop adopters and Hadoop-related vendors.

The results got me thinking two things:
– how does the geographic spread compare to a more maturely adopted project?
– how does it compare to the various NoSQL projects?

So I did some searching of LinkedIn to find out.

To answer the first question I performed the same search for MySQL, as an example of a mature, widely-adopted open source project.

The results show that just 32% of the 366,084 LinkedIn members with “MySQL” in their member profiles are based in the US (precisely half that of Hadoop) while only 4.4% are in the Bay area, compared to 28.2% of the 9,079 LinkedIn members with “Hadoop” in their member profiles.

The charts below illustrate the difference in geographic distribution between Hadoop and MySQL. The size of the boxes is in proportion to the search result (click each image for a larger version).

With regards to the second question, I also ran searches for MongoDB, Riak, CouchDB, Apache Cassandra*, Membase*, Neo4j, Hbase, and Redis.

I’ll be posting the results for each of those over the next week or so, but in the meantime, the graphic below shows the split between the USA and Rest of the World (ROW) for all ten projects.

It illustrates, as I suspected, that the distribution of skills for NoSQL databases is more geographically disperse than for Hadoop.

I have some theories as to why that is – but I’d love to hear anyone else’s take on the results.

*I had to use the ‘Apache’ qualifier with Cassandra to filer out anyone called Cassandra, while Membase returned a more statistically relevant result than Couchbase.

World map image: Owen Blacker

As we noted last week, necessity is one of the six key factors that are driving the adoption of alternative data management technologies identified in our latest long format report, NoSQL, NewSQL and Beyond.

Necessity is particularly relevant when looking at the history of the NoSQL databases. While it is easy for the incumbent database vendor to dismiss the various NoSQL projects as development playthings, it is clear that the vast majority of NoSQL projects were developed by companies and individuals in response to the fact that the existing database products and vendors were not suitable to meet their requirements with regards to the other five factors: scalability, performance, relaxed consistency, agility and intricacy.

The genesis of much – although by no means all – of the momentum behind the NoSQL database movement can be attributed to two research papers: Google’s BigTable: A Distributed Storage System for Structured Data, presented at the Seventh Symposium on Operating System Design and Implementation, in November 2006, and Amazon’s Dynamo: Amazon’s Highly Available Key-Value Store, presented at the 21st ACM Symposium on Operating Systems Principles, in October 2007.

The importance of these two projects is highlighted by The NoSQL Family Tree, a graphic representation of the relationships between (most of) the various major NoSQL projects:

Not only were the existing database products and vendors were not suitable to meet their requirements, but Google and Amazon, as well as the likes of Facebook, LinkedIn, PowerSet and Zvents, could not rely on the incumbent vendors to develop anything suitable, given the vendors’ desire to protect their existing technologies and installed bases.

Werner Vogels, Amazon’s CTO, has explained that as far as Amazon was concerned, the database layer required to support the company’s various Web services was too critical to be trusted to anyone else – Amazon had to develop Dynamo itself.

Vogels also pointed out, however, that this situation is suboptimal. The fact that Facebook, LinkedIn, Google and Amazon have had to develop and support their own database infrastructure is not a healthy sign. In a perfect world, they would all have better things to do than focus on developing and managing database platforms.

That explains why the companies have also all chosen to share their projects. Google and Amazon did so through the publication of research papers, which enabled the likes of Powerset, Facebook, Zvents and Linkedin to create their own implementations.

These implementations were then shared through the publication of source code, which has enabled the likes of Yahoo, Digg and Twitter to collaborate with each other and additional companies on their ongoing development.

Additionally, the NoSQL movement also boasts a significant number of developer-led projects initiated by individuals – in the tradition of open source – to scratch their own technology itches.

Examples include Apache CouchDB, originally created by the now-CTO of Couchbase, Damien Katz, to be an unstructured object store to support an RSS feed aggregator; and Redis, which was created by Salvatore Sanfilippo to support his real-time website analytics service.

We would also note that even some of the major vendor-led projects, such as Couchbase and 10gen, have been heavily influenced by non-vendor experience. 10gen was founded by former Doubleclick executives to create the software they felt was needed at the digital advertising firm, while online gaming firm Zynga was heavily involved in the development of the original Membase Server memcached-based key-value store (now Elastic Couchbase).

In this context it is interesting to note, therefore, that while the majority of NoSQL databases are open source, the NewSQL providers have largely chosen to avoid open source licensing, with VoltDB being the notable exception.

These NewSQL technologies are no less a child of necessity than NoSQL, although it is a vendor’s necessity to fill a gap in the market, rather than a user’s necessity to fill a gap in its own infrastructure. It will be intriguing to see whether the various other NewSQL vendors will turn to open source licensing in order to grow adoption and benefit from collaborative development.

NoSQL, NewSQL and Beyond is available now from both the Information Management and Open Source practices (non-clients can apply for trial access). I will also be presenting the findings at the forthcoming Open Source Business Conference.

The NoSQL EU event in London this week was a great event with interesting perspectives from both vendors – Basho, Neo Technology, 10gen, Riptano – and also users – The Guardian, the BBC, Amazon, Twitter. In particular I was interested in learning from the latter about how and why they ended up using alternatives to the traditional relational database model.

Some of the reasons for using NoSQL have been well-documented: Amazon CTO Werner Vogels talked about how the traditional database offerings were unable to meet the scalability Amazon.com requires. Filling a functionality void also explains why Facebook created Cassandra, Google created BigTable, and Twitter created FlockDB (etc etc). As Werner said, “We couldn’t bet the company on other companies building the answer for us.”

As Werner also explained, however, the motivation for creating Dynamo was also about enabling choice and ensuring that Amazon was not trying to force the relational database to do something it was not designed to do. “Choosing the right tool for the job” was a recurring theme at NoSQL EU.

Given the NoSQL name it is easy to assume that this means that the relational database is by default “the wrong tool”. However, the most important element in that statement is arguably not “tool”, but “job” and The Guardian discussed how it was using non-relational data tools to create new applications that complement its ongoing investment in the Oracle database.

For example, the Guardian’s application to manage the progress of crowdsourcing the investigation of MP’s expenses is based on Redis, while the Zeitgeist trending news application runs on Google’s AppEngine, as did its live poll during the recent leader’s election debate. Datablog, meanwhile, relies on Google Spreadsheets to serve up usable and downloadable data – we’ll ignore for a moment whether Google Spreadsheets is a NoSQL database 😉

Long-term The Guardian is looking towards the adoption of a schema-free database to sit alongside its Oracle database and is investigating CouchDB. The overarching theme, as Matthew Wall and Simon Willison explained, is that the relational database is now just a component in the overall data management story, alongside data caching, data stores, search engines etc.

On the subject of choosing the right tool for the job, Basho’s engineering manager Brian Fink pointed out that using NoSQL technology alongside relational SQL database technology may actually improve the performance of the SQL database since storing data in a relational database that does not need SQL features slows down access to data that does need SQL features.

Another perspective on this came from Werner Vogels who noted that unlike database administrators/ systems architects, users don’t care about where data resides or what model it uses – as long as they get the service they require. Werner explained that the Amazon.com homepage is a combination of 200-300 different services, with multiple data systems. Users do not think about data sources in isolation, they care about the amalgamated service.

This was also a theme that cropped up in the presentation by Enda Farrell, software architect at the BBC, who noted that the BBC’s homepage is a PHP application integrated with multiple data sources at multiple data centers, and also Twitter‘s analytics lead Kevin Weil, who described Twitter’s use of Hadoop, Pig, HBase, Cassandra and FlockDB.

While the company is using HBase for low-latency analytic applications such as people search and moving to Cassandra from MySQL for its online applications, it uses its recently open-sourced FlockDB graph database to serve up data on followers and correlate the intersection of followers to (for example) ensure that Tweets between two people are only sent to the followers of both. (As something of an aside, Twitter is using Hadoop to store the 7TB of of data its generates a day from Tweets, and Pig for non-real time analytics).

Kevin noted that the company is also working with Digg to build real-time analytics for Cassandra and will be releasing the results as open source, and also discussed how Twitter has made use of open source technologies created by others such as Facebook (both Cassandra and the Scribe log data aggregation server.

One of the issues that has arisen from the fact that organizations such as Amazon and Facebook have had to create their own data management technologies is the proliferation of NoSQL databases and a certain amount of wheel re-invention.

Werner explained that SmugMug creator Don Macaskill ended up being a MySQL expert not because he necessarily wanted to be, but because he needed to be because he had to be to keep his applications running.

“He doesn’t want to have to become an expert in Cassandra,” noted Werner. “What he wants is to have someone run it for him and take care of that.” Presumably Riptano, the new Cassandra vendor formed by Jonathan Ellis – project chair for the Cassandra database – will take care of that, but in the meantime Werner raised another long-term alternative.

“We shouldn’t all be doing this,” he said, adding that Dynamo is not as popular within Amazon Web Services as it once was as it is a product, that requires configuration and management, rather than a service, and Amazon employees “have better things to do.”

Which raises the question – don’t Twitter, Facebook, the BBC, the Guardian et al have better things to do than developing and maintaining database architecture? In a perfect world, yes. But in a perfect world they’d all have strongly consistent, scalable distributed database systems/services that are suited to their various applications.

Interestingly, describing S3 as “a better key/value store than Dynamo”, Werner noted that SimpleDB and S3 are “a good start to provide that service”.

I was asked a few weeks ago whether I thought NoSQL was largely a US, (and specifically) West Coast phenomenon. While it might seem that way for some of those in the bubble that is the Bay Area (and to be fair that’s where I was at the time), the answer is a definite “no”.

As if to prove it, NoSQL EU is being held London next week with a great program of presentations from NoSQL vendors, projects and users.

April 20 features presentations on The Guardian’s use of NoSQL, as well as an overview from Alex Popescu of MyNoSQL, followed by presentations from Basho, 10gen, Rackspace and Neo Technology.

April 21 sees Amazon CTO Werner Vogels describing the birth of Dynamo, as well as presentations on the use of NoSQL databases from the BBC, Twitter, and Comcast. That is followed by presentations on Redis, Tokyo Cabinet (et al) and “the fate of the relational database”. Oh, and a panel debate moderated by some bloke called James Governor 😉

Then on the 22nd there’s a day of workshops involving MongoDB, Redis, Riak and Neo4J.

It’s shaping up to be a great event and I’m really looking forward to it. If you’re going to be there and want to say hi (between sessions!) let me know.

One of the essential problems with the covering the NoSQL movement is that it describes not what the associated databases are, but what they are not (and doesn’t even do that very well since SQL itself is in many cases orthogonal to the problem the databases are designed to solve).

It is interesting to see fellow analyst Curt Monash facing the same problem. As he notes, while there seems to be a common theme that “NoSQL is Foo without joins and transactions,” no one has adequately defined what “Foo” is.

Curt has proposed HVSP (High-Volume Simple Processing) as an alternative to NoSQL, and while I’m not jumping on the bandwagon just yet, it does pass the Ronseal test (it does what it says on the tin), and it also matches my view of what defines these distributed data store technologies.

Some observations:

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There are numerous categorizations of the various NoSQL technologies available on the Internet. Without wishing to add yet another to the mix, I have created another one – more for my benefit than anything else.

It includes a list of users for the various projects (where available), and also some sense of whether the various projects fit into CAP Theorem, an understanding of which is, to my mind, essential for understanding how and why the NoSQL/HVSP movement has emerged (look out for more on CAP Theorem in a follow-up post on alternatives to NoSQL).

Here’s my take, for those that are interested. As you can see there’s a graph database-shaped whole in my knowledge. I’m hoping to fill that sooner rather than later.

By the way, our Spotlight report introducing The 451 Group’s formal coverage of NoSQL databases will be available here imminently.

Update: VMware has announced that it has hired Redis creator Salvatore Sanfilippo, and is taking on the Redis key value store project. The image below has been updated to reflect that, as well as the launch of NorthScale’s Membase.