Top 3 Ways Ant-Man and MapR are Similar

As you probably know (unless you’ve been living under an ant hill), Ant-Man is a fictional superhero who first appeared in Marvel comic books, and he’s also a proud founding member of The Avengers. He made his debut on the big screen recently with the advent of this summer’s blockbuster movie, “Ant-Man,” which has, as of last week, already earned $116.8 million at the domestic box office, and $234 million worldwide.

Clearly people love Ant-Man, who has the astonishing ability to shrink in scale, but increase in strength. If you think about it, a similar situation is occurring in the big data world, where the average organization is expected to grow their data by 50 percent in the coming year, according to Forrester Research. But instead of being forced to buy additional storage capacity every 6 to 12 months, organizations are turning to Apache Hadoop in order to process huge amounts of data by connecting many commodity computers together to work in parallel. With MapR, innovations at the file system for faster file access, and an optimized MapReduce shuffle engine let you get more work with less hardware than compared to other distributions.

Let’s take a look at the synergies between these two seemingly very different, yet similar “technologies”:

  1. Ant-Man and MapR both have the ability to scale. In fact, the largest ant colony ever found was over 3,750 miles wide. Similarly, as the most advanced distribution for Hadoop, MapR gives you the ability to start with one node to build an application and quickly deploy to a production environment with thousands of nodes. In addition, ants are known to be surprisingly efficient, and as you may know, MapR is 2-11x more efficient than other Hadoop distributions. Lastly, don’t forget that the MapR Data Platform supports trillions of files and tables, which is likely to cause even Ant-Man to be a little jealous.
  2. Both Ant-Man and MapR have no single point of failure. Ant-Man’s systems of ants must be robust to scale up as the colony grows, and they have to be able to tolerate the failure of individual components (ants). Similarly, the MapR distributed metadata architecture allows for extreme scalability with no practical limit on the number of files that can be stored on Hadoop; the larger the cluster, the faster recovery occurs from a single node failure.
  3. Ant-Man and MapR feature great communication. Ants have an ultra-sophisticated communication method that uses pheromones, sounds, and touch to communicate with other ants in their colony. In terms of MapR communication, we offer secure and encrypted transmission between servers, and pluggable authentication to secure your platform. With MapR, there’s no need to run multiple clusters. In fact, we see 96% of MapR customers running multiple use cases on a single Hadoop cluster, with 18% running over 50 use cases on a single cluster.

Now there’s one thing that Ant-Man can do that MapR can’t: Ant-Man can just think about what he wants the ants to do in order to control them. Although at MapR, we’re known for our game-changing innovation, so give us a few years – we may surprise you.

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Driving The Next Generation Data Architecture with Hadoop
This paper examines the emergence of Hadoop as an operational data platform, and how complementary data strategies and year-over-year adoption can accelerate consolidation and realize business value.

Streaming Data Architecture:

New Designs Using Apache Kafka and MapR Streams

 

 

 

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