Apache Hadoop 1.0. The future of CouchDB (or Couchbase anyway). And more.

Welcome to the first in an occasional series of data-related news, views and links posts on Too Much Information. You can also follow the series @thedataday.

* The Apache Software Foundation Announces Apache Hadoop v1.0 Self-explanatory.

* The Future of CouchDB Apache CouchDB creator Damien Katz explains why he is focusing his attention on Couchbase Server.

* Understanding Microsoft’s big-picture plans for Hadoop and Project Isotope Mary Jo Foley parses Alexander Stojanovic’s presentation.

* MongoDB Extends Leadership in NoSQL 10gen claims more than 400 commercial customers.

* 1010data’s Unique Big Data Analytics Platform Sees Stunning Growth in 2011 1010data runs the numbers on its adoption in 2011.

* TouchDB 1.0 is out TouchDB is a lightweight CouchDB-compatible database engine suitable for embedding into mobile apps.

* Data Scientist = Rock Star, Really? Virginia Backaitis is sceptical.

* Swimming with Dolphins Splunk’s connector for MySQL.

* What the Sumerians can teach us about data Pete Warden finds data inspiration at the British Museum.

* How To (Not) Get Smart About Big Data Wim Rampen on the importance of filtering noise.

* For 451 Research clients

# Total Data: exploratory analytic platforms Spotlight report

# Apache Hadoop reaches version 1.0, with more to come Analyst note

# Acunu hones focus on ‘big data’ platform for operational analytics Market development report

# Jaspersoft gets big into ‘big data,’ illuminates BI business momentum Market development report

* Google News Search outlier of the day: “Bella” Becomes Most Popular Name for Both Dogs and Cats

And that’s the Data Day, today.

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

451 Research has today published a report looking at the funding being invested in Apache Hadoop- and NoSQL database-related vendors. The full report is available to clients, but below is a snapshot of the report, along with a graphic representation of the recent up-tick in funding.

According to our figures, between the beginning of 2008 and the end of 2010 $95.8m had been invested in the various Apache Hadoop- and NoSQL-related vendors. That figure now stands at more than $350.8m, up 266%.

That statistic does not really do justice to the sudden uptick of interest, however. The figures indicate that funding for Apache Hadoop- and NoSQL-related firms has more than doubled since the end of August, at which point the total stood at $157.5m.

A substantial reason for that huge jump is the staggering $84m series A funding round raised by Apache Hadoop-based analytics service provider Opera Solutions.

The original commercial supporter of Apache Hadoop, Cloudera, has also contributed strongly with a recent $40m series D round. In addition, MapR Technologies raised $20m to invest in its Apache Hadoop distribution, while we know that Hortonworks also raised a substantial round (unconfirmed, but reportedly $20m) from Benchmark Capital and former parent Yahoo as it was spun off in June. Index Ventures also recently announced that it has become an investor in Hortonworks.

I am reliably informed that if you factor in Hortonworks’ two undisclosed rounds, the total funding for Hadoop and NoSQL vendors is actually closer to $400m.

The various NoSQL database providers have also played a part in the recent burst of investment, with 10gen raising a $20m series D round and Couchbase raising $15m. DataStax, which has interests in both Apache Cassandra and Apache Hadoop, raised an $11m series B round, while Neo Technology raised a $10.6m series A round. Basho Technologies raised $12.5m in series D funding in three chunks during 2011.

Additionally, there are a variety of associated players, including Hadoop-based analytics providers such as Datameer, Karmasphere and Zettaset, as well as hosted NoSQL firms such as MongoLab, MongoHQ and Cloudant.

One investor company name that crops up more than most in the list above is Accel Partners, which was an original investor in both Cloudera and Couchbase, and backed Opera Solutions via its Accel- KKR joint venture with Kohlberg Kravis Roberts.

It appears that those investments have merely whetted Accel’s appetite for big data, however, as the firm last week announced a $100m Big Data Fund to invest in new businesses targeting storage, data management and analytics, as well as data-centric applications and tools.

While Accel is the fist VC shop that we are aware of to create a fund specifically for big data investments, we are confident both that it won’t be the last and that other VCs have already informally earmarked funds for data-related investments.

451 clients can get more details on funding and M&A involving more traditional database vendors, as well as our perspective on potential M&A suitors for the Hadoop and NoSQL players.

Recently there have been a spate of postings regarding job trends for distributed data management technologies including Hadoop and the various NoSQL databases.

One thing you rarely see on these job trends charts is comparison with an incumbent technology, for context. There’s a reason for that, as this comparison of database-related jobs from Indeed.com illustrates:

Although there has been a recent increase in job postings related to Hadoop and MongoDB, both are dwarfed, in absolute terms, by the number of job postings involving SQL Server and MySQL.

So why all the fuss about Hadoop and NoSQL, from a corporate perspective? This chart, showing the relative growth for the same data management technologies, says it all:

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.

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.

As a company, The 451 Group has built its reputation on taking a lead in covering disruptive technologies and vendors. Even so, with a movement as hyped as NoSQL databases, it sometimes pays to be cautious.

In my role covering data management technologies for The 451 Group’s Information Management practice I have been keeping an eye on the NoSQL database movement for some time, taking the time to understand the nuances of the various technologies involved and their potential enterprise applicability.

That watching brief has now spilled over into official coverage, following our recent assessment of 10gen. I also recently had the chance to meet up with Couchio’s VP of business development, Nitin Borwankar (see coverage initiation of Couchio). I’ve also caught up with Basho Technologies sooner rather than later. A report on that is now imminent.

There are a couple of reasons why I have formally began covering the NoSQL databases. The first is the maturing of the technologies, and the vendors behind them, to the point where they can be considered for enterprise-level adoption. The second is the demand we are getting from our clients to provide our view of the NoSQL space and its players.

This is coming both from the investment community and from existing vendors, either looking for potential partnerships or fearing potential competition. The number of queries we have been getting related to NoSQL and big data have encouraged articulation of my thoughts, so look-out for a two-part spotlight on the implications for the operational and analytical database markets in the coming weeks.

The biggest reason, however, is the recognition that the NoSQL movement is a user-led phenomena. There is an enormous amount of hype surrounding NoSQL but for the most part it is not coming from vendors like 10gen, Couchio and Basho (although they may not be actively discouraging it) but from technology users.

A quick look at the most prominent key-value and column-table NoSQL data stores highlights this. Many of these have been created by user organizations themselves in order fill a void and overcome the limitations of traditional relational databases – for example Google (BigTable), Yahoo (Hbase), Zvents (Hypertable), LinkedIn (Voldemort), Amazon (Dynamo), and Facebook (Cassandra).

It has become clear that traditional database technologies do need meet the scalability and performance requirements of dealing with big data workloads, particularly at a scale experienced by social networking services.

That does raise the question of how applicable these technologies will be to enterprises that do not share the architecture of the likes of Google, Facebook and LinkedIn – at least in the short-term. Although there are users – Cassandra users include Rackspace, Digg, Facebook, and Twitter, for example.

What there isn’t – for the likes of Cassandra and Voldemort, at least – is vendor-based support. That inevitably raises questions about the general applicability of the key-value/column table stores. As Dave Kellog notes, “unless you’ve got Google’s business model and talent pool, you probably shouldn’t copy their development tendencies”.

Given the levels of adoption it seems inevitable that vendors will emerge around some of these projects, not least since, as Dave puts it, “one day management will say: ‘Holy Cow folks, why in the world are we paying programmers to write and support software at this low a level?’”

In the meantime, it would appear that the document-oriented data stores (Couchio’s CouchDB, 10gen’s MongoDB, Basho’s Riak) are much more generally applicable, both technologically and from a business perspective. UPDATE – You can also add Neo Technology and its graph database technology to that list).

In our forthcoming two-part spotlight on this space I’ll articulate in more detail our view on the differentiation of the various NoSQL databases and other big data technologies and their potential enterprise applicability. The first part, on NoSQL and operational databases, is here.

Back in July last year we reported on the formation of a new open source cloud computing start-up called 10gen on our Cloud Cover and CAOS Theory blogs.

Seven months later and there have been a few changes at 10gen, such that this information management blog is arguably the most suitable venue for discussion of the implications of 10gen’s MongoDB, the cloud computing database which has now become its major focus.

A quick recap: 10gen launched as an open source platform-as-a-service play offering the MongoDB object database as well as an application server and file system. So far, so cloud stack.

However, the file system quickly became an interface layer to MongoDB while the company more recently decided that its application server runtime and MongoDB are better off apart and shifted its attention to the database, a standalone beta version of which was released last week.

As the two projects have diverged so will this post. To continue reading about the future of the Babble application server head for CAOS Theory, otherwise:

As this post from Geir Magnusson Jr, 10gen VP of Engineering & Co-Founder, at Codehaus describes, MongoDB is not your traditional database.

“As I argue when people give me the chance to speak about it, databases are changing – just look at what is available in the so-called “cloud” arena. It tends not to be a RDBMS if it’s scalable. The storage engine under AppEngine, or Amazon’s SimpleDB, or any of the Dynamo implementations, etc, all of which change your programming model to one that isn’t “tables and joins”. Or look at the excellent CouchDB, a JSON store. If the RDBMS isn’t being replaced outright (like it has to be in “the cloud”), it can to be augmented with other persistence technologies that are better suited for a portion of the data requirements of a system.”

This was one of the themes of my talk at our client event in Boston last year, and nothing has happened since then to change my mind. As Geir explains, the interesting thing about the new cloud databases (for want of a better term) is that they force users to think differently about what a database is for – and specifically to think beyond the realms of the relational.

We see similar forces at work in the data warehousing space driven by column-oriented architectures, but the end result is the same as users are increasingly thinking beyond what already know to consider the best database management tools for the job at hand.

As Geir adds of MongoDB: “It works fine as a database, but you can’t think relational. If you want to just replace MySQL with something else, but don’t want to rethink your data model, MongoDB isn’t for you.”