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Relational Databases to Riak
This is a presentation given by Matt Brender (@mjbrender) at Big Data TechCon 2015.
In this class, we will discuss why companies choose Riak over a relational database with a specific focus on availability, scalability, and the key/value data model. We then analyze the decision points that should be considered when choosing a non-relational solution and review data modeling, querying, and consistency guarantees. Finally, we end with simple patterns for building common applications in Riak using its key/value design, dealing with data conflicts that emerge in an eventually consistent system, and discuss multi-datacenter replication.
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Introduction to Riak - Red Dirt Ruby Conf Training
An introduction to the concepts behind Riak, Basho's distributed database, with a focus on using the database with Ruby.
Recommended
Relational Databases to Riak
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In this class, we will discuss why companies choose Riak over a relational database with a specific focus on availability, scalability, and the key/value data model. We then analyze the decision points that should be considered when choosing a non-relational solution and review data modeling, querying, and consistency guarantees. Finally, we end with simple patterns for building common applications in Riak using its key/value design, dealing with data conflicts that emerge in an eventually consistent system, and discuss multi-datacenter replication.
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Distributed Key-Value stores are the new breed of Clustered databases for the Internet.
Riak - From Small to Large
Riak ( http://wiki.basho.com ), a Dynamo-inspired, open-source key/value datastore, was built to scale from a single machine to a 100+ server cluster without driving you or your operations team crazy. This presentation discusses the characteristics of Riak that become important in small, medium, and large clusters.
Introduction to Riak - Red Dirt Ruby Conf Training
An introduction to the concepts behind Riak, Basho's distributed database, with a focus on using the database with Ruby.
Eventually Consistent Data Structures (from strangeloop12)
There are many reasons to use an eventually-consistent database — like Riak, Voldemort, or Cassandra — including increased availability, lower latency, and fault-tolerance. However, doing so requires a mental shift in how to structure client applications, and certain types of traditional data-structures, like sets, registers, and counters can’t be resolved simply in the face of race-conditions. It is difficult to achieve “logical monotonicity” except for the most trivial data-types.
That is, until the advent of Convergent Replicated Data Types (CRDTs). CRDTs are data-structures that tolerate eventual consistency. They replace traditional data-structure implementations and all have the property that, given any number of conflicting versions of the same datum, there is a single state on which they converge (monotonicity). This talk will discuss some of the most useful CRDTs and how to apply them to solve real-world data problems.
Eventually-Consistent Data Structures
There are many reasons to use an eventually-consistent database -- like Riak, Voldemort, or Cassandra -- including increased availability, lower latency, and fault-tolerance. However, doing so requires a mental shift in how to structure client applications, and certain types of traditional data-structures, like sets, registers, and counters can't be resolved simply in the face of race-conditions. It is difficult to achieve "logical monotonicity" except for the most trivial data-types.
That is, until the advent of Conflict-Free Replicated Data Types (CRDTs). CRDTs are data-structures that tolerate eventual consistency. They replace traditional data-structure implementations and all have the property that, given any number of conflicting versions of the same datum, there is a single state on which they converge (monotonicity). This talk will discuss some of the most useful CRDTs and how to apply them to solve real-world data problems.
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whether Threads, Fibers, event loops, or actors are the best solution. But did you ever consider that your *sequential* Ruby program might be concurrent, with nary a Thread, Fiber, or callback in sight? Well, it happened to me.
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We'll look closely at how Riak, a linearly-scalable, distributed and fault-tolerant NoSQL datastore, implements eventual consistency, and how you can harness it from Ruby via the slick Ripple client/ORM. When the talk is finished, you'll have the tools both to understand eventual consistency and to handle it like a pro inside your next Ruby application.
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Moving to Riak involves a number of changes from the status quo of RDBMS systems, one of which is taking greater control over your schema design.
* How do you structure data when you don't have tables and foreign keys?
* When should you denormalize, add links, or create map-reduce queries?
* Where will Riak be a natural fit and where will it be challenging?
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An introduction to Basho's Riak distributed data store, and the Ripple client in Ruby. Code samples from the demos are here: http://gist.github.com/365791
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Many developers will be familiar with lex, flex, yacc, bison, ANTLR, and other related tools to generate parsers for use inside their own code. For recognizing computer-friendly languages, however, context-free grammars and their parser-generators leave a few things to be desired. This is about how the seemingly simple prospect of parsing some text turned into a new parser toolkit for Erlang, and why functional programming makes parsing fun and awesome
Story Driven Development With Cucumber
Software projects are rarely on-spec, on-time and on-budget, and the primary cause is miscommunication. As Martin Fowler says, there is a "yawning crevasse of doom" between stakeholders and developers, full of misunderstanding. How do you make sure that you're building something that adds value? How do you know you're building the thing that was asked for? How does your bottom line affect user experience?
Into the fray leaps Cucumber, a business-readable DSL combined with an awesome Ruby library that lets domain experts express business requirements as executable user stories. We'll cover outside-in, story-driven development with Cucumber, how to write effective stories, and how to make Cucumber work for your project.
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That is, until the advent of Conflict-Free Replicated Data Types (CRDTs). CRDTs are data-structures that tolerate eventual consistency. They replace traditional data-structure implementations and all have the property that, given any number of conflicting versions of the same datum, there is a single state on which they converge (monotonicity). This talk will discuss some of the most useful CRDTs and how to apply them to solve real-world data problems.
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Concurrency in Ruby is all the rage these days, and people can't seem to agree
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A discussion of strategies for designing application schemas that use the Riak distributed key-value store.
Video available here: http://vimeo.com/17604126
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* How do you structure data when you don't have tables and foreign keys?
* When should you denormalize, add links, or create map-reduce queries?
* Where will Riak be a natural fit and where will it be challenging?
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