On one side:

1. DataStax with Solr
2. MapR with LucidWorks Search (nb: Solr)

and on the other side:

1. Riak Searching: Solr-like but custom prioprietary implementation
2. MongoDB text search: custom prioprietary implementation

I’m not going to argue about the pros and cons of each of these approaches, but I’m sure you already know which of these approaches I’m in favor of.

Original title and link: NoSQL and Full Text Indexing: Two Trends (NoSQL database©myNoSQL)

Where is MapR today?

1. MapR raised a total of $59mil.
2. According to John Schroeder (CEO) “92% of MapR customers pay primarely for licenses and not for ancillary services and support”.
3. According to Wikibon, MapR had $23mil. revenue in 2012, 49% of which coming from services (nb: this seem to contradict the above point)
4. Support for MapR installations is offered by Accenture and Booz Allen Hamilton

How will MapR use the new capital?

With the new funding, the company plans to invest in research & development, and expand into Asia.

How is MapR seeing its competitors?

John Schroeder (CEO):

“Our competitors’ model is very cash intensive and you have to wonder whether or not they’ll ever be cash-flow positive”.

Clouder has raised until now $141mil as follow:

1. Series A: $5mil
2. Series B: $6mil
3. Series C: $25mil
4. Series D: $40mil
5. Series E: $65mil

According to this, Cloudera raised $36mil in the first 3 rounds. I couldn’t find any official data about the capital raised by Hortonworks, but the number I’ve seen in a couple of places is $50mil. So far MapR raised $59mil.

Sources for these bits:

• VentureBeat: MapR gets $30M to push Hadoop deeper into the enterprise
• AllThingsD: MapR Lands $30 Million Series C Led by Mayfield Fund - Arik Hesseldahl - Enterprise - AllThingsD
• CrunchBase: Cloudera | CrunchBase Profile
• Wikibon: Big Data Vendor Revenue And Market Forecast 2012-2017 - Wikibon

Original title and link: MapR Raises $30mil in Series C (NoSQL database©myNoSQL)

The short answer is there is only one Apache Hadoop distribution.

The long answer is that there are many distributions that include Apache Hadoop or are claiming compatibility with Apache Hadoop.

The oldest and probably most popular: Cloudera’s Distribution of Hadoop (CDH)

The 100% open source: Hortonworks Data Platform.

The prioprietary: MapR.

The blue one: IBM InfoSphere BigInsights.

The latest: WANdisco Hadoop WDD, Intel Distribution of Hadoop and Pivotal HD from EMC Greenplum.

There’s also the version Facebook’s running on their cluster which includes Facebook Corona: a different approach to job scheduling and resource management.

But this list is not complete as it doesn’t include appliances featuring Hadoop. In this category we have:

1. Oracle’s Big Data appliance featuring Cloudera’s Distribution of Hadoop
2. Netapp’s Hadooplers
3. EMC Greenplum DCA
4. Teradata Aster Discovery Platform featuring Hortonworks’s Hadoop Data Platform
5. Data Direct Networks (DDN)

I hope I didn’t miss any important ones¹. As a conclusion for this list, my question is: who is actually benefiting from all these distributions?

Original title and link: How Many Hadoops? (NoSQL database©myNoSQL)

MapR is definitely up to some interesting partnerships. Last year it announced a partnership with EMC for Greenplum HD Enterprise Edition, then this year MapR became available on Amazon Elastic MapReduce and Google Compute Engine. And today MapR and Drawn to Scale, creator of the real-time database for Hadoop Spire, are announcing a new partnership.

Bradford Stephens (CEO, Drawn to Scale):

MapR provides the fastest, most reliable Hadoop for our customers. We are thrilled to work with MapR to deliver M3 as part of Spire as the first real-time database for Hadoop.

Jack Norris (VP of marketing, MapR Technologies):

Real-time SQL on Hadoop is a big gap in the market that is addressed by Spire. Spire is a complementary solution to our products and it made sense to work with Drawn to Scale to make it easier for customers to deploy M3, pre-integrated with Spire, for real-time SQL-based workloads.

It might sound strange coming from me, but MapR is making quite some big steps towards becoming the de facto standard for Hadoop. I’m looking forward to seeing the reactions from Cloudera and Hortonworks.

Original title and link: MapR’s New Partnership With Drawn to Scale (NoSQL database©myNoSQL)

A couple of links covering various aspects of this question:

1. Quora thread covering this subject
2. Joe Stein’s Hadoop distribution bake-off and my experience with Cloudera and MapR
3. How I’d choose a Hadoop distribution
4. MapR claims title as de facto standard for Hadoop

If you have other good references answering the question of what Hadoop distribution to choose please leave a comment.

Original title and link: Cloudera or MapR for Hadoop Distribution? (NoSQL database©myNoSQL)

Another very interesting news for the Hadoop space, this time coming from Amazon and MapR announcing support for the MapR Hadoop distribution on Amazon Elastic MapReduce:

MapR introduces enterprise-focused features for Hadoop such as high availability, data snapshotting, cluster mirroring across AZs, and NFS mounts. Combined with Amazon Elastic MapReduce’s managed Hadoop environment, seamless integration with other AWS services, and hourly pricing with no upfront fees or long-term commitments, Amazon EMR with the MapR Distribution for Hadoop offers customers a powerful tool for generating insights from their data.

Following the logic of the Amazon Relational Database Services which started with MySQL, the most popular and open source database and then added support for the commercial, but also very popular Oracle and SQL Server, what does this announcement tell us? It’s either that Amazon has got a lot of requests for MapR or that some very big AWS customers have mentioned MapR in their talks with Amazon. I go with the second option.

Original title and link: MapR Hadoop Distribution on Amazon Elastic MapReduce (NoSQL database©myNoSQL)