Three years after we (re)started tracking mentions of NoSQL database in LinkedIn member profiles it is time to retire the NoSQL LinkedIn Skills Index – at least in terms of regular updates.

We started tracking mentions of NoSQL database in LinkedIn member profiles in order to keep an eye on trends that could shape the industry, but after three years it has become clear that in terms of LinkedIn member profiles there is only one trend: the total dominance of MongoDB.

Once again MongoDB was responsible for more than 50% of all mentions of NoSQL database in LinkedIn member profiles in Q3, placing it way, way ahead of the nearest competitor.

As always there were changes of position further down the rankings, with OrientDB overtaking Accumulo and RethinkDB overtaking Voldemort. We are talking about very small numbers, however. To be honest tracking these numbers has become something of a chore given the lack of change, and even the addition of Microsoft Azure DocumentDB and Google Cloud Bigtable couldn’t lift our interest

For the record, the fastest growth in the quarter was recorded by RethinkDB, with mentions up 36.2%, followed by multi-model players OrientDB (28.0%) and ArangoDB (23.0%), as well as Aerospike (22.1%). Inside the top ten, DynamoDB had the fastest growth (16.5%).

However, since none of the top 10 look like changing places any time soon, and none of the players outside stand any chance of breaking into the top 10, the time has come to retire the NoSQL LinkedIn Skills Index.

Perhaps we’ll pull it out and freshen it up on special occasions, however.

Of course, we would also note that this is not meant to be a comprehensive analysis, but rather a snapshot of one particular data source.

It finally happened: 11 quarters in to our NoSQL LinkedIn Skills Index, which tracks mentions of NoSQL database in LinkedIn member profiles, MongoDB finally hits the 50% mark, representing half of all mentions of NoSQL databases in Q1.

That wasn’t the only change in the rankings in Q1 as there were no fewer than three changes of position in the rankings. In the top 10 DynamoDB overtook MarkLogic to claim ninth place, while lower down OrientDB overtook Aerospike in 12th place, while ArangoDB overtook Sparksee to enter the top 20.

In fact, ArangoDB recorded the highest rate of growth in the quarter, with LinkedIn mentions up 77.4%. We would expect it to overtake FoundationDB in Q2 even if the latter hadn’t just been taken out of the market by Apple. As such we’ll remove it from the rankings next quarter anyway.

It was a good quarter for other multi-model databases as well as ArangoDB as OrientDB climbed a place thanks to 42.5% growth. Aerospike lost that place to OrientDB despite recording the third fastest growth rate, with 29.6%. Other fast climbers were FoundationDB, Titan (despite Aurelius being acquired by DataStax – incidentally Titan will remain in the rankings since it remains available) and RethinkDB.

Inside the top ten, DynamoDB had the fastest growth (20.2%) and stands a chance of gaining another place next quarter by overtaking Riak.

Of course, we would also note that this is not meant to be a comprehensive analysis, but rather a snapshot of one particular data source.

There’s an early end to the quarter for our NoSQL LinkedIn Skills Index, based on the number of LinkedIn member profiles mentioning each of the NoSQL projects, just as there was in 2012.

We predicted in Q3 that Couchbase would overtake MarkLogic this quarter, which came to pass, but were somewhat surprised to see Couchbase also leapfrog Riak to claim 7th place. It’s almost too close to call between the three, though we wouldn’t be surprised to see those places change hands in the coming quarters.

There were no other changes of position outside the top ten, although Titan is bearing down on Hypertable having recorded the fastest growth in Q4 (49.5%) and can be expected to gain a place in Q1 2014. The second fastest climber, in terms of mentions, was FoundationDB, followed by ArangoDB, RethinkDB and Apache Cassandra (the latter being particularly notable since it was the only one of the five fastest growers to also be one of the top ten most mentioned in LinkedIn member profiles).

That growth was of course not enough to close the gap on MongoDB as the most mentioned NoSQL database in LinkedIn member profiles, although for the first time MongoDB’s proportion of the overall total actually declined – from 49% in Q3 to 48%, upsetting our prediction that MongoDB would pass the 50% threshold in Q4.

It will be interesting to see whether MongoDB’s dominance declines again in Q1, although either way it retains a monumental lead over all the other NoSQL databases in terms of mentions in LinkedIn profiles.

Of course, we would also note that this is not meant to be a comprehensive analysis, but rather a snapshot of one particular data source.

With our rebooted NoSQL LinkedIn Skills Index, based on the number of LinkedIn member profiles mentioning each of the NoSQL projects, now into its second year, I thought it was a good time to add some newer projects to the list; specifically: ArangoDB, FoundationDB, RethinkDB, and Titan.

It shouldn’t surprise anyone to find that those four new additions failed to make a dent in the top ten list of the NoSQL databases most often cited in LinkedIn profiles. However, there is still some interesting activity this quarter, with Riak leapfrogging MarkLogic (as predicted).

Outside the top ten, Apache Accumulo overtook Voldemort, and saw the second fastest growth in mentions in Q3, behind only DynamoDB and ahead of Neo4j, MongoDB, and Cassandra.

That growth saw MongoDB extend its lead as the most popular NoSQL database, according to LinkedIn profile mentions. As the chart below illustrates, it now accounts for 49% of all mentions of NoSQL technologies in LinkedIn profiles, according to our sample, compared with 47% in June.

Incidentally, adding the four new NoSQL databases to the analysis did not have a significant impact on MongoDB’s share. Without them it still registered 49%. Expect MongoDB to pass the 50% threshold in Q4, however, as well as Couchbase to overtake MarkLogic.

Of course, we would also note that this is not meant to be a comprehensive analysis, but rather a snapshot of one particular data source.

Four quarters have now passed since we rebooted our NoSQL LinkedIn Skills Index, based on the number of LinkedIn member profiles mentioning each of the NoSQL projects, giving us a good view of the relative growth of the various NoSQL databases in the past year.

A few interesting statistics to pick out: Cassandra has jumped ahead of Redis for second place, while outside the top ten, shown here, OrientDB climbed above Hypertable and DEX climbed above InfiniteGraph. Looking ahead, expect Riak to overtake MarkLogic in the next three months.

DynamoDB saw the greatest increase in terms of the number of mentions in LinkedIn profiles in the past three months, although it remains in 10th position. In terms of growth, DynamoDB was followed by OrientDB, Neo4j, Apache Accumulo and DEX.

However, MongoDB once again extended its lead as the most popular NoSQL database, according to LinkedIn profile mentions. As the chart below illustrates, it now accounts for 47% of all mentions of NoSQL technologies in LinkedIn profiles, according to our sample, compared with 46% in March.

Of course, we would also note that this is not meant to be a comprehensive analysis, but rather a snapshot of one particular data source.

Another significant data source that can provide a different perspective on the NoSQL market is our market-sizing revenue estimate. Stand-by for an update on our sizing estimates for the NoSQL, NewSQL, MySQL and DBaaS sectors in the coming weeks.

As Q1 comes to a close its time to take another look at our NoSQL LinkedIn Skills Index, based on the number of LinkedIn member profiles mentioning each of the NoSQL projects. This is the second update since we rebooted the analysis in September 2012 to account for more products and refine our search terms.

A few interesting statistics to pick out: Neo4j has, as predicted, jumped ahead of MarkLogic for sixth place. No other changes of position, but outside the top ten, shown here, Apache Accumulo continues to grow well.

In fact, Apache Accumulo had the fastest rate of growth for the second quarter in succession, just ahead of DynamoDB and OrientDB -once again – followed by Apache Cassandra and MongoDB.

MongoDB’s growth means that it once again extended its lead as the most popular NoSQL database, according to LinkedIn profile mentions. As the chart below illustrates, it now accounts for 46% of all mentions of NoSQL technologies in LinkedIn profiles, according to our sample, compared with 45% in December.

Time again to take a look at our NoSQL LinkedIn Skills Index, based on the number of LinkedIn member profiles mentioning each of the NoSQL projects. This is the first update since we rebooted the analysis in September to account for more products and refine our search terms.

On the face of it not a lot has changed in the last quarter, although there are a few interesting statistics to pick out. For instance, Neo4j is now practically tied for sixth place with MarkLogic and can be expected to overtake it in Q1 2013. Outside the top ten shown above, Apache Accumulo has gained two places – overtaking Aerospike and Hypertable.

In fact, Apache Accumulo showed the fastest rate of growth in mentions between September and December, just ahead of DynamoDB and OrientDB, followed by Couchbase and MongoDB.

MongoDB’s growth means that it has cemented its place as the most popular NoSQL database, according to LinkedIn profile mentions. As the chart below illustrates, it now accounts for 45% of all mentions of NoSQL technologies in LinkedIn profiles, according to our sample, compared with 43% in September.

I decided to reboot our analysis of NoSQL skills, according to LinkedIn search results.

There are two main reasons for doing so: the first iteration did not take in enough of the various NoSQL projects; and I have – with help – worked my way around the eccentricities of LinkedIn search to produce a more accurate result for Apache Cassandra.

The analysis therefore now incorporates a wider spectrum of NoSQL projects, the top ten most popular of which are displayed below. The chart illustrates the number of LinkedIn member profiles mentioning each of the NoSQL projects:

The main change from the previous results is the promotion of Apache Cassandra, thanks to our better search string, while MarkLogic is the first of our new additions to make the top ten.

What hasn’t changed is the dominance of MongoDB, which is way-ahead of all the others. While I am not breaking out growth percentages versus previous counts due to the reboot, it is fair to say that MongoDB is outpacing many of its rivals. Neo4j and DynamoDB are also growing particularly well.

In fact, as can be seen from the chart below, MongoDB accounts for 43% of all mentions of NoSQL technologies in LinkedIn profiles, according to our sample.

Back in December we published an assessment on the distribution of Hadoop skills, based on LinkedIn search results.

Thanks to a temporary lull in GB’s Olympic medal-winning exploits I ran the search again the other day. The results are pretty interesting for a number of reasons.

First the headline stats:

• There are over 22,000 people with Hadoop in their LinkedIn profiles, up from just over 9,000 in December 2011, an increase of over 144% in eight months.
• Hadoop skills are becoming more evenly distributed: 60.4% of LinkedIn members with Hadoop in the profiles are based in the US, compared to 64.5% in December 2011.
• Growth areas include India (11.9% from 9.7%), China (4.4% from 3.6%, and the UK (3.4% from 3.0%).
• However, the Bay Area remains the best place to find Hadoop enthusiasts, with 24.9% (albeit down from 28.2% eight months ago)

This time I also ran a similar search for MapReduce skills. The headline results:

• MapReduce is mentioned in 6,424 LinkedIn profiles.
• MapReduce skills are more evenly distributed: 61.9% of LinkedIn members with MapReduce in their profiles are based in the US, 38.1% in the rest of the world.
• That said, over a quarter (25.9%) of LinkedIn members with MapReduce in their profiles are based in the Bay area.
• Other geographic hotspots are India (8.7%), Seattle area (5.8%), and NYC area (4.8%).

This time I also looked at which vendors are listed as the current employers of LinkedIn members citing Hadoop and MapReduce. One really surprising result stood out:

• Microsoft is the second largest employer of both Hadoop and MapReduce skills, according to LinkedIn member profiles
• Redmond employs 1.7% of all LinkedIn members with Hadoop in their profiles, and 3.0% of members with MapReduce in their profiles
• Yahoo is the largest employer of Hadoop skills (2.9%), with other ‘non-vendors’ also well represented: Google (1.3%), eBay (also 1.3%), Amazon (1.2%), LinkedIn (1.1%).
• Google is by far the largest employer of MapReduce skills, as you might expect, with 7.1%. Also well represented are Yahoo (2.7%), Amazon (1.8%) and LinkedIn (1.4%).

A few weeks ago I updated our previous analysis of LinkedIn search results to take us up to the end of Q2 2012, but for one reason or another I didn’t get around to posting the results. As you can see from the results, there isn’t anything particularly controversial to say about them, other than that MongoDB continues to extend its lead over the rest in terms of the number of mentions in LinkedIn member profiles.

One thing that isn’t immediately clear from the chart is that Neo4j overtook Riak in the second quarter to claim sixth place by a narrow margin. Also, Apache HBase has consolidated its third place position having overtaken Apache CouchDB in the first quarter.

Neo4j’s ascendency is due to it having the fastest growth rate of all the NoSQL projects in Q2, according to our search results. The number of Neo4j mentions in LinkedIn profiles grew 65.8% between our March and June searches, followed by MongoDB (59.5%) and Redis (59.1%).

As you can see, I have also added Amazon’s DynamoDB to the list for this iteration. It will be interesting to see how it performs going forward. As usual, it should be noted that 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.

I have also adjusted once again how we assess Couchbase/Membase, having belatedly realised that LinkedIn supports boolean searches. As of this point forward, the result represents a search for Membase OR Couchbase.

Once again, we would also note that this is not meant to be a comprehensive analysis, but rather a snapshot of one particular data source.