July 17th, 2014 — Data management
Introducing the Total Data Warehouse. And more
And that’s the data day, today.
May 8th, 2014 — Data management
Teradata and Tableau report Q1 results
And that’s the data day, today.
December 18th, 2013 — Data management
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.
October 18th, 2013 — Data management
Apache Hadoop 2 goes GA. Teradata cuts guidance. And more
And that’s the data day, today.
October 1st, 2013 — Data management
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.
September 6th, 2013 — Data management
Where database startups go to die. And more.
And that’s the data day, today.
March 26th, 2013 — Data management
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.
January 14th, 2013 — Data management
Navigating our illustrated database landscape map. And more
And that’s the Data Day, today.
January 4th, 2013 — Data management
Apache Cassandra and BigTop updates. And more
And that’s the Data Day, today.
September 28th, 2012 — Data management
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.
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