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Recap: Cloud Foundry Summit 2015, Day 2

Alex Khizhniak

CF Summit: Ideation wall

                 Day 1 | Day 2 | Top 100 Quotes

According to Diego Lapiduz—who presented at CF Summit on Monday—one of his colleagues recently said: “If you take Cloud Foundry from us, we will hurt you.” Quite convincing to hear this from anyone working within US GSA!

Still, every joke has its share of truth. Those who work with Cloud Foundry become its advocates. Keynotes and sessions delivered on the 2nd day proved that once again. Read on to learn what May 12 brought to 1,500 attendees of the summit.

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NoSQL Tech Comparison 2014: Cassandra (DataStax), MongoDB, and Couchbase

Alex Khizhniak

Introducing a NoSQL scoring framework

Even if you have years of experience with data-intensive apps, selecting a NoSQL data store for a particular case out of dozens of options may be a daunting task. The variety of databases goes way beyond sheer numbers, so you have to carefully compare and benchmark several options before you can choose the most appropriate solution.

To help companies select the best database based on particular use cases, workloads, or requirements, we decided to come up with a handy template for evaluating NoSQL solutions. While many other comparisons focus only on one or two dimensions, we compiled a scoring framework that approaches the databases from 20+ angles (including performance, scalability, availability, ease of installation, maintenance, data consistency, fault tolerance, replication, recovery, etc.).

As a real-life example of such an evaluation benchmark, today we present “The NoSQL Technical Comparison Report,” which provides an in-depth analysis of the leading NoSQL systems: Cassandra (DataStax), MongoDB, and Couchbase Server. Each of the databases was scored on a scale from 1 to 10 across 21 criteria.

With 29 charts and 30 tables, this paper features a scoring template for evaluating and comparing NoSQL data stores for your particular use case—depending on the weight of each criterion. We also give recommendations on the best ways to configure, install, and use NoSQL databases depending on their specific features.

 

Want details? Watch a webinar!

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LikeFolio: Invest in What You "Like" (Fox Business Video)

Alex Khizhniak

A scalable architecture based on Redis

Recently, Fox Business interviewed Nicole Sherrod of TD Ameritrade on online stock trading. In the video below, she is talking about the success of LikeFolio, a web project that assists online investors by analyzing social media data.

Altoros was proud to help SwanPowers, a partner of TD Ameritrade, to build this application, which is based on the “invest in what you know” concept. The system aggregates your conversations, status updates, likes, and check-ins from social networks and translates this data into investment ideas (using IPO information).

likefolio-redis-amazon-ruby-altoros

LikeFolio was written with Ruby and features a distributed, scalable architecture able to serve 10,000+ users simultaneously. To provide scalability and service availability, LikeFolio was deployed on Amazon’s infrastructure and utilized Redis—a scalable NoSQL store—for caching and network scalability (the pub/sub model).

Read the customer story in our portfolio to learn more about other technologies used.

 

Want details? Watch the video!

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Hadoop Benchmark: Cloudera vs. Hortonworks vs. MapR

Alex Khizhniak

Evaluating Hadoop distributions across 7 workloads

Cloudera, Hortonworks, and MapR are the most popular Hadoop distributions available today. However, even with this short list, there are few unbiased comparisons of their cluster performance. So, today we’re introducing a 65-page research paper that contains a vendor-independent overview of Cloudera, Hortonworks, and MapR distributions.

cloudera_hortonworks_mapr

Vladimir Starostenkov of Altoros compared throughput of 8-, 12-, and 16-node clusters against performance of a 4-node cluster. (The speed of data processing of 8-, 12-, and 16-node clusters was divided by the throughput of a 4-node cluster.) The results were quite unexpected.

 

Hadoop cluster performance: bigger doesn’t mean faster

In a recent interview to TechTarget, our R&D Engineer Dmitriy Kalyada explained why adding nodes to a Hadoop cluster not always results in better performance. The new benchmark of Hadoop distributions confirms this behavior under several workloads.

For instance, when sorting unstructured text data (the Sort workload), the performance of a MapR cluster was growing linearly (as we were increasing its size from 4 to 8 nodes). After that, when new machines were added, the throughput of each separate node was degrading.

mapr_performance

As you can see on the diagram, an 8-node cluster turned out to be faster than clusters of 12 and 16 nodes. The same situation was observed in the DFSIO write test. Other Hadoop distributions had similar results under some of the workloads, too.

Download the benchmark to see all the performance results (83 diagrams, 7 types of workloads), including:

  • detailed performance results for 4-, 8-, 12-, and 16-node clusters
  • how the size of a cluster affects data processing speed
  • how different clusters behave under CPU and disk-bound workloads (including Bayes, DFSIO, Hive aggregation, PageRank, Sort, TeraSort, and WordCount)
  • what issues slow down deployment and how to maximize Hadoop processing speed

Get your copy of “Hadoop Distributions: Cloudera vs. Hortonworks vs. MapR” and let us know what you think about these results.

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Big Data in Denmark: Notes from IT Messe 2013

Alex Khizhniak

Although the big data market in Denmark is still young now, it is definitely growing.

On Oct 9–10, the IT Messe conference attracted 40+ exhibitors and ~500 attendees to the Horsens city. At the event, Kim Jonassen, our Managing Director Denmark, spoke on the state of big data in Denmark. He overviewed the type of systems and companies that struggle with big data and also explained how distributed processing, NoSQL data stores, and other tools address these issues.

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Benchmarking Couchbase Server vs. Cassandra vs. MongoDB for Interactive Apps (2013)

Alex Khizhniak

Looking for a new database for your data-intensive application? Don’t miss our new research paper revealing performance test results for Cassandra, MongoDB, and Couchbase Server.

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Altoros at the Panel on Cloud Computing for Startups

Alex Khizhniak

On September 24, 2011, Altoros supported the Cloud Startup meetup held in Minsk, Belarus (Eastern Europe). Kirill Grigorchuk, the head of our Research & Development department, gave the session entitled, “Cloud Computing: The Brief Overview of the Main Services and Their Key Features.” After that, together with Vitaly Sedelnik, Team Lead at Altoros, they participated in the panel “SaaS Apps: Development Stages and Horizons.”

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Altoros Has Launched a Ruby on Rails Training

Alex Khizhniak


Can’t find Ruby developers for your project? We understand. To help our customers hire enough RoR staff, Altoros has launched a series of Ruby on Rails training courses. We pre-selected  the best-of-breed developers (Senior and Mid level) that previously worked with other technologies (PHP, Java, etc.) to help them enter the Ruby world. In the course of 3 months, they will get the comprehensive overview of Ruby on Rails and start working on the projects. We’ll post a bit later about the results.

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Altoros at Linux Vacation 2011

Alex Khizhniak

During June 30 – July 3, 2011, Altoros supported LVEE-2011 (Linux Vacation Eastern Europe). The conference gathered together FOSS experts from Hungary, Russia, Ukraine, Estonia, Lithuania, and Belarus.

Aliaksey Kandratsenka, Senior RoR Developer at Altoros and an active contributor to Couchbase (Membase), presented the Cells.js library–as a way to develop modern applications. At the event, Kirill Grigorchuk, the head of the Reasearch & Development dep at Altoros, spoke on the directions our R&D team works in. Three other RoR developers from our team contributed to the conference as attendees. =)

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Introducing Our R&D Team and Innovative Technology BarCamps

Alex Khizhniak
Kirill Grigorchuk

Kirill Grigorchuk,
Head of R&D

Recently, we’ve created the Research & Development department within Altoros to keep track of the latest technologies available on the market. The main goal of the department is to learn how projects can be developed faster, better, more effectively, and more efficiently.

The team of the highly skilled developers across different technologies (Ruby, Java/NoSQL, etc.) investigate the trends and share their ideas on the tools/frameworks they tried and the results they achieved.

As part of these R&D activities, we regularly hold barcamps within Altoros to help developers stay on the cutting edge: they share their experience and ideas, discuss challenging tasks and implemented solutions, make reports, etc. In addition, our R&D department actively involved and takes part in organizing and sponsoring industry conferences and IT events, as well as holds own meetups and hackathons.

We do believe that our R&D team will help us find new promising technologies/approaches for our customers and suggest new solutions even before some of these technologies become a trend among your competitors.

Learn more about R&D department at Altoros here.

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