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| <h1>Meet the Druid and Find Out Why We Set Him Free</h1> |
| <p class="text-muted">by <span class="author text-uppercase">Steve Harris</span> · April 26, 2013</p> |
| |
| <p>Before jumping straight into why <a href="http://metamarkets.com/">Metamarkets</a> open |
| sourced <a href="https://github.com/metamx/druid/wiki">Druid</a>, I thought I would give a |
| brief dive into what Druid is and how it came about. For more details, check |
| out the <a href="http://static.druid.io/docs/druid.pdf">Druid white paper</a>.</p> |
| |
| <h3 id="introduction">Introduction</h3> |
| |
| <p>We are lucky to be developing software in a period of extreme innovation. |
| Fifteen years ago, if a developer or ops person went into his or her boss’s |
| office and suggested using a non-relational/non-SQL/non-ACID/non-Oracle |
| approach to storing data, they would pretty much get sent on their way. All |
| problems at all companies were believed to be solved just fine using relational |
| databases.</p> |
| |
| <p>Skip forward a few years and the scale, latency and uptime requirements of the |
| Internet really started hitting the |
| <a href="http://research.google.com/archive/spanner.html">Googles</a> and |
| <a href="http://www.read.seas.harvard.edu/%7Ekohler/class/cs239-w08/decandia07dynamo.pdf">Amazons</a> |
| of the world. It was quickly realized that some compromises needed to be made |
| to manage the challenging data issues they were having in a cost-effective way. |
| It was also finally acknowledged that different use cases might benefit from |
| different solutions.</p> |
| |
| <p>Druid was born out of this era of data stores, purpose-built for a specific set |
| of trade-offs and use cases. We believe that taking part in and keeping pace |
| with this period of innovation requires more than a company. It requires a |
| community.</p> |
| |
| <h3 id="so-what-are-druids-core-values">So What Are Druid's Core Values?</h3> |
| |
| <p>Druid was built as an analytics data store for Metamarkets’ as-it-happens, |
| interactive SaaS platform targeted at the online advertising industry. It |
| fundamentally needs to ingest tens of billions of events per day per customer |
| and provide sub-second, interactive, slicing and dicing on arbitrary queries. |
| It has to do this in an efficient and cost effective way.</p> |
| |
| <p>Values: |
| - 24x7x365x10 (Hours/days, days/a week, days/year, years) |
| - User speed responses (millis not micros) on arbitrary analytics queries |
| - Billions of events per day per customer as they happen (fast append) |
| - Cost-effective data management |
| - Linear scale-out |
| - Predictable responses |
| - Community/Adoption wins</p> |
| |
| <p>Non-Values: |
| - Not a key-value store |
| - Not focused on fast update or delete</p> |
| |
| <p>We looked at a lot of options and many of them had some of these properties but none had all.</p> |
| |
| <h3 id="cost-is-no-joke">Cost Is No Joke</h3> |
| |
| <p>When looking at the success of data management platforms like Hadoop, it is |
| important not to underestimate how important cost is. While Hadoop is powerful, |
| it was certainly true that other platforms were managing huge amounts of data |
| before its existence. One of Hadoop’s fundamental innovations was being able to |
| manage that data for a much lower cost per gigabyte compared to existing |
| solutions. This was achieved by a combination of the hardware it could run on, |
| the flexible programming model, and of course, the fact that it’s open source |
| and can be used for free.</p> |
| |
| <p>Druid also takes the value proposition of cost seriously. It compresses rolled |
| up data to use as little CPU and storage space as it can. It also runs well on |
| commodity boxes and is open source. The combination of these two factors make |
| it a cost effective solution to user time querying of 100s of terabytes of |
| data. This makes the difficult and expensive practical.</p> |
| |
| <h3 id="druid-today">Druid Today?</h3> |
| |
| <p>Druid has been in production living up to its core values at Metamarkets for a |
| few years now. Since going open source, we’ve had the pleasure of seeing |
| adoption in a number of different organizations and for different use cases. |
| Not least of which culminated in co-presenting on <a href="http://www.youtube.com/watch?v=Dlqj34l2upk">how Netflix engineers use |
| Druid</a> at Strata in February, 2013. |
| It has proven to be an excellent platform, processing 10s of billions of |
| events/day, storing 100s of TB of data, and providing fast, predictable |
| arbitrary querying.</p> |
| |
| <p>So why did we open source it?</p> |
| |
| <h3 id="why-oss">Why OSS?</h3> |
| |
| <p>I'm glad you asked. It might seem counter intuitive to open source something so |
| valuable. We feel like we have some good reasoning.</p> |
| |
| <ul> |
| <li>While we have some very specific use cases for Druid, we felt like it was |
| broadly applicable. Opening it up helps us learn what those other use cases |
| are.</li> |
| <li>Having others put pressure on it from other verticals is an excellent way to |
| keep the data store ahead of our needs. Since the platform is so important to |
| us, we want to make sure it has momentum and life.</li> |
| <li>We hope that by open sourcing it, we will get outside contributions both in |
| code and ideas.</li> |
| </ul> |
| |
| <p>Druid is a very important piece of the Metamarkets platform. That said, it will |
| always be cheaper and easier for people to use the Metamarkets SaaS solution |
| rather than building and managing a cluster oneself. However, for those who |
| have use cases not directly covered by what Metamarkets offers, open source |
| Druid helps users create software that can leverage the power of a real-time, |
| scalable analytics-oriented data store. Looking for more Druid information? |
| <a href="http://metamarkets.com/product/technology/">Learn more about our core technology</a>.</p> |
| |
| <p><a href="http://www.flickr.com/photos/nengard/5755231610/">PHOTOGRAPH BY NICOLE C. ENGARD</a></p> |
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