The Data Day: February 10, 2017

SEE YOU IN COURT, THE FUTURE OF DATA AND ANALYTICS AT STAKE!

And that’s the data day, today.

The Data Day: January 20, 2017

The same people who did the phony election data, and were so wrong, are now doing approval rating analytics. They are rigged just like before.

And that’s the data day, today.

NoSQL LinkedIn Skills Index – An Interesting Occasional Update

I was recently prompted by OrientDB CEO Luca Garulli to take another look at the NoSQL LinkedIn Skills Index, which we previously updated on a regular basis between September 2012 and 2015.

I wouldn’t read too much into the results since there’s been such a long period between updates, and this is – as ever – just a snapshot of one particular data source. However, they are definitely interesting, especially when you consider that we retired the NoSQL LinkedIn Skills Index primarily because the results had become so boringly predictable.

As such I’d make the following observations without any additional comment:

  • It is interesting to note that MongoDB’s share of mentions of NoSQL databases in LinkedIn member profiles has declined since September 2015, from 51% to 48%. Of course, MongoDB remains the number one by a considerable margin.
  • It is also interesting to note that Redis has climbed above Cassandra to claim second spot.
  • Similarly it is interesting that Neo4j has climbed above CouchDB for fifth place.
  • And it is also interesting that DynamoDB has overtaken Couchbase for eighth place.
  • It is also interesting that the two fastest growing NoSQL databases, in terms of mentions in LinkedIn profiles, are Google Cloud Bigtable (up 557%) and Azure DocumentDB (up 254%).
  • And it is also interesting that the third fastest growth came from RethinkDB, despite the recent demise of the company of the same name.
  • Those growth rates saw Google Clooud Bigtable climb above Voldemort, ArangoDB, Hypertable and Allegrograph, while Azure DocumentDB climbed above Titan and Voldemort, and RethinkDB climbed above Titan and Accumulo.

Since Luca prompted another look at the results, I should also probably point out that mentions of OrientDB grew at a healthy 83% as OrientDB held on to 11th place in the Index.

Interesting…

The Data Day: October 7, 2016

What happened in data and analytics this week will astound you

And that’s the data day, today.

The Data Day, A few days: January 16-22, 2016

Funding for Qubole, ScaleArc, GigaSpaces, MariaDB. And more.

And that’s the data day, today.

NoSQL LinkedIn Skills Index – September 2015

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.

sept donut

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.

sept skills index

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.

NoSQL LinkedIn Skills Index – June 2015

MongoDB has maintained its feat from last quarter of being responsible for more than 50% of all mentions of NoSQL database in LinkedIn member profiles.

june doughnut

As with Q1 there were once again three changes of position in the rankings in Q2. DynamoDB overtook Riak to claim eighth place, having also gained a place (on MarkLogic) in the previous quarter.

Further down the list ArangoDB also gained a place for the second successive quarter – this time on AllegroGraph, while Titan gained a place on Voldemort. As noted in the previous blog post, FoundationDB has been removed from the analysis following its acquisition.

The fastest growth in the quarter was recorded by RethinkDB, with mentions up 46.1%, followed by multi-model players OrientDB (33%) and ArangoDB (32.7%), as well as Aerospike (26%). Inside the top ten, DynamoDB had the fastest growth (17.0%).

june index

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.

The Data Day, A few days: April 11-22, 2015

CenturyLink, Hortonworks and Percona acquire Orchestrate, SequenceIQ and Tokutek respectively

And that’s the data day, today.

NoSQL LinkedIn Skills Index – March 2015

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.

nosqlwheel

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.

nosqlline

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.

NoSQL LinkedIn Skills Index – December 2014

As usual there’s an early finish to the quarter for our NoSQL LinkedIn Skills Index, which tracks mentions of NoSQL database in LinkedIn member profiles, but as usual that has little impact on the results as MongoDB continues to account for 49% of all LinkedIn member profiles mentioning a NoSQL project.

Q4donut

There are a few changes further down the list of NoSQL projects with both Aerospike and OrientDB overtaking Voldemort, as predicted, and RethinkDB overtaking Hypertable.

As noted last quarter, there was a chance that Aerospike might get overtaken by OrientDB and MarkLogic might get overtaken by DynamoDB. As it happens both held off their respective challengers but their places remain under threat.

ArangoDB had the fastest rate of growth in the quarter (21.57%), followed by RethinkDB (21.28%), FoundationDB (19.74%), OrientDB (18.02%) and Aerospike (17.62%). DynamoDB was next, and the fastest growing inside the top ten, with 14.37%.

q4chart

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.