Tag Archives: Riak 2.0

Basho at NYLUG

February 5, 2014

At the recent meetup for the New York Linux Users Group (NYLUG), Basho Technical Evangelist, Tom Santero, presented “An Introduction to Basho’s Riak.” In this talk, Tom explains how Riak addresses the challenges of concurrent data storage at scale. He discusses the various design decisions, tradeoffs made, and theories at work within Riak. He also provides guidance as to how you might deploy Riak in production and why.

In addition to introducing the basics of Riak and its key/value data model, Tom presents some of the exciting features being introduced with Riak 2.0. Riak Data Types adds counters, sets, and maps to Riak – allowing for better conflict resolution. They enable developers to spend less time thinking about the complexities of vector clocks and sibling resolution and, instead, focusing on using familiar, distributed data types to support their applications’ data access patterns.

You can watch Tom’s full talk below:

For more information about Riak and how it differs from traditional databases, check out the whitepaper, “From Relational to Riak.”

To see where Basho will be presenting next, visit the Events Page.

Basho

Hangouts with Basho

January 29, 2014

On Fridays, Basho hosts a Hangout to discuss various topics related to Riak and distributed systems. While Basho evangelists and engineers lead these live Hangouts, they also bring in experts from various other companies, including Kyle Kingsbury (Fatcual), Jeremiah Peschka (Brent Ozar Unlimited), and Stuart Halloway (Datomic).

If you haven’t attended a Hangout, we have recorded them all and they are available on the Basho Technologies Youtube Channel. You can also watch each below.

Data Types and Search in Riak 2.0

Featuring Mark Phillips (Director of Community, Basho), Sean Cribbs (Engineer, Basho), Brett Hazen (Engineer, Basho), and Luke Bakken (Client Services Engineer, Basho)

Bucket Types and Configuration

Featuring Tom Santero (Technical Evangelist, Basho), Joe DeVivo (Engineer, Basho), and Jordan West (Engineer, Basho)

Riak 2.0: Security and Conflict Resolution

Featuring John Daily (Technical Evangelist, Basho), Andrew Thompson (Engineer, Basho), Justin Sheehy (CTO, Basho), and Kyle Kingsbury (Factual)

Fun with Java and C Clients

Featuring Seth Thomas (Technical Evangelist, Basho), Brett Hazen (Engineer, Basho), and Brian Roach (Engineer, Basho)

Property Based Testing

Featuring Tom Santero (Technical Evangelist, Basho) and Reid Draper (Engineer, Basho)

Datomic and Riak

Featuring Hector Castro (Technical Evangelist, Basho), Dmitri Zagidulin (Professional Services, Basho), and Stuart Halloway (Datomic)

CorrugatedIron

Featuring John Daily (Technical Evangelist, Basho), David Rusek (Engineer, Basho), and Jeremiah Peschka (Brent Ozar Unlimited)

A Look Back

Featuring John Daily (Technical Evangelist, Basho), Hector Castro (Technical Evangelist, Basho), Andy Gross (Chief Architect, Basho), and Mark Phillips (Director of Community, Basho)

Hangouts take place on Fridays at 11am PT/2pm ET. If you have any topics you’d like to see featured, let us know on the Riak Mailing List.

Basho

RICON West Videos: Strong Consistency in Riak

January 6, 2014

With the launch of the Technical Preview of Riak 2.0, we also announced the addition of strong consistency to Riak. This addition fundamentally changes how Riak can be used, since all previous versions classified Riak as an eventually consistent system.

With Riak 2.0, developers now have the flexibility to choose whether buckets should be highly available or strongly consistent, based on data requirements. Consistency preferences are defined on a per bucket type basis, in the same cluster.

At RICON West 2013, Basho senior engineer, Joseph Blomstedt, gave an updated version of his “Bringing Consistency to Riak” talk. The original talk (presented at RICON West 2012) discussed the challenges, motivations, and high-level plans of bringing consistency to Riak. This updated version presents the actual implementation that has since been built and how it will function in Riak 2.0. Both talks are available below.

To start testing the strong consistency feature, you can download the Technical Preview of Riak 2.0 here.

To watch all of the sessions from RICON West 2013, visit the Basho Technologies Youtube Channel.

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RICON West Videos: Riak Search 2.0

December 17, 2013

In addition to Riak Data Types, there were a number of other presentations about Riak 2.0 features at RICON West. With the Technical Preview of Riak 2.0, we also announced a completely redesigned Riak Search.

Riak is a straight key/value data store and all objects are stored on disk as binaries. It is content agnostic – meaning you can store any type of data as the value in Riak. To improve the usability and functionality of Riak, we offer multiple querying options including Riak Search, Secondary Indexing, and MapReduce. Riak Search is a full-text search that allows Riak developers to index the contents of stored values. While Riak Search offers much needed functionality, it had its flaws.

In Riak 2.0, Riak Search received a complete overhaul. Riak Search 2.0 leverages the Apache Solr full-text document indexing engine directly. Riak users now get the power of Solr, with the availability and scalability of Riak. This upgrade also supports the Solr client-queries API, which enables integration with existing software solutions.

Eric Redmond is one of the Basho engineers who works on Riak Search. At RICON, he presented “Riak Search 2.0,” which walks through what’s new with Riak Search and why you’d want to use it. He also provides some impressive demos that show off the power of Solr and Riak. His full talk is below.

For more information on Riak Search 2.0, check out these resources on Github.

To watch all of the sessions from RICON West 2013, visit the Basho Technologies Youtube Channel.

Basho

RICON West Videos: Riak Data Types

December 12, 2013

At RICON West this year, we announced the Technical Preview of Riak 2.0. Before the full release (which will be available early next year), we are encouraging users to download the preview and start testing some of the exciting new features.

At RICON, we had many of the engineers who worked on these new features present their work. One feature that we’re particularly excited about is the addition of Riak Data Types. Riak 2.0 builds on eventually consistent counters (added with Riak 1.4) with the addition of maps and sets. These Riak Data Types simplify application development without sacrificing Riak’s availability and partition tolerance characteristics.

In “CRDTs: An Update (or Maybe Just a PUT),” Basho engineer, Sam Elliott, presents on the work being done with Riak Data Types. Sam and a few other engineers at Basho have been integrating cutting-edge research on data types (known as CRDTs), pioneered by INRIA, to create Riak Data Types. Sam talks about the latest developments on CRDTs and walks developers through how to use them in their own applications.

In addition to Sam’s talk, we also had a talk from Jeremy Ong on “CRDTs in Production.” His talk provides real world solutions to leveraging CRDT concepts for an industrial application via case study. He also offers some suggestions on how to tackle data operations that can’t always commute. You can watch his full talk below.

For more information about Riak Data Types, check out this overview on Github.

To watch all of the sessions from RICON West 2013, visit the Basho Technologies Youtube Channel.

Basho

Relational to Riak – Tradeoffs

November 18, 2013

This series of blog posts will discuss how Riak differs from traditional relational databases. For more information about any of the points discussed, download our technical overview, “From Relational to Riak.” The previous post in the series discussed High Availability and Cost of Scale.


Eventual Consistency

In order to provide high availability, which is a cornerstone of Riak’s value proposition, the database stores several copies of each key/value pair.

This availability requirement leads to a fundamental tradeoff: in order to continue to serve requests in the presence of failure, we do not force all data in the cluster to stay in sync. Riak will allow writes and reads no matter how many servers (and their stored replicas) are offline or otherwise unreachable.

(Incidentally, this lack of strong coordination has another consequence beyond high availability: Riak is a very, very fast database.)

Riak does provide both active and passive self-healing mechanisms to minimize the window of time during which two servers may have different versions of data.

The concept of eventual consistency may seem unfamiliar, but if you’ve ever implemented a cache or used DNS, those are common examples of the idea. In a large enough system, it’s effectively the default state of all data.

However, with the forthcoming release of Riak 2.0, operators will be able to designate selected pieces of data to require coordination and maintain strong consistency over high availability. Writing such data will be slower and subject to failure if too many servers are unreachable, but the overall robust architecture of Riak will still provide a fast, highly available solution.

Data Modeling

Riak stores data using a simple key/value model, which offers developers tremendous flexibility to define access models that suit their applications. It is also content-agnostic, so developers can store arbitrary data in any convenient format.

Instead of forcing application-specific data structures to be mapped into (and out of) a relational database, they can simply be serialized and dropped directly into Riak. For records that will be frequently updated, if some of the fields are immutable and some aren’t, we recommend keeping the immutable data in one key/value pair and the rest organized into a single or multiple objects based on update patterns.

Relational databases are ingrained habits for many of us, but moving beyond them can be liberating. Further information about data modeling, including sample configurations, are available on Use Cases section of the documentation.

Tradeoffs

One tradeoff with this simpler data model is that there is no SQL or SQL-like language with which to query the data.

To achieve optimal performance, it is advisable to take advantage of the flexibility of the key/value model to define simple retrieval patterns. In other words, determine the most useful queries and write the results of those queries as the data is being processed.

Because it is not always possible to know in advance what questions will need to be asked of your data, Riak offers added functionality on top of the key/value model. Tools such as Riak Search (a distributed, full-text search engine), Secondary Indexing (ability to tag objects with queryable metadata), and MapReduce (leveraged for aggregation tasks) are available to perform ad hoc queries as needed.

For many users, the tradeoffs of moving to Riak are worthwhile due to the overall benefits; however, it can be a bit of an adjustment. To see why others have chosen to switch to Riak from both relational systems and other NoSQL databases, check out our Users Page.

Basho

A Weekly Hangout With Basho

November 11, 2013

Last Friday, the Basho team held our inaugural Riak Community Hangout.

This 30 minute session is a development focused conversation with topics changing weekly. The Hangout is planned for most Fridays at 11am Pacific/2pm Eastern/7pm GMT, with the URL published shortly before it begins. All Hangouts will be archived and hosted on the Basho Technologies Youtube channel. You should follow @basho for all updates about future Hangouts.

Over the next few weeks, these Hangouts will focus on the new features planned for Riak 2.0.

The first session was hosted by Basho’s Director of Community, Mark Phillips, who discussed Riak Data Types and Riak Search 2.0 with Basho engineers Sean Cribbs, Brett Hazen, and Luke Bakken.

The Hangout began with an overview of Riak Data Types, available with the 2.0 Technical Preview, and examined their implementation, use cases, and implementation considerations. Following this (at 18 minutes, 35 seconds), Brett Hazen provided an overview of Riak Search 2.0 (codenamed Yokozuna) and Luke Bakken queried a portion of the Twitter stream on a cluster running the newest Riak Search 2.0 code.

Upcoming sessions will focus on Riak/Riak CS internals, application building, data modeling, and community requested topics. We are also looking for community members to join in and highlight what you’re building with Riak and Riak CS developers

If you have questions or topics you would like to hear discussed, reach out on the message list, in IRC (#riak on irc.feenode.net), or contact us.

Basho

RICON West: Day Two

October 30, 2013

Today is the second day of RICON West, Basho’s distributed systems conference. If you weren’t able to make it out to San Francisco for the conference, tune in to our live stream to watch all of the great talks.

Day One of RICON West was an exciting one. Basho announced the availability of the Riak 2.0 Technical Preview (which Eric Redmond and Joseph Blomstedt described in more detail during their talks) and James Hughes of Seagate did the first live demo of the Kinetic Open Storage platform and Riak.

We also heard some amazing sessions from Pat Helland (Salesforce), Lindsey Kuper (Indiana University), Miles O’Connell (StackMob), Justin Shoffstall (Basho), Charlie Voiselle (Basho), Jeff Hodges (Twitter), Peter Bailis (UC Berkeley), Ryland Degnan (Netflix), and Derek Murray (Microsoft Research). We wrapped up Day One with Lightning Talks from across the industry and celebrated at Twenty Five Lusk (thanks for the drinks, Tower3 and Github!).

Today is another full day of amazing talks. Check out talks from Justin Sheehy (Basho), Diego Ongaro (Stanford University), Jeremy Ong (TBA), Jordan West (Basho), Susan Potter (Finsignia), Jason Brown (Netflix), Richard Simon (State Farm Insurance), Richard Berglund (State Farm Insurance), Michael Bernstein (Code Climate), Sam Elliott (Basho), Andrew Thompson (Basho), Raja Selvaraj (The Weather Company), and Arvinda Gillella (The Weather Company). Additionally, Google Fellow, Jeff Dean, will be delivering the closing keynote on “The Tail at Scale: Achieving Rapid Response Times in Large Online Services.”

Be sure and watch it all on our live stream and follow along on Twitter with #riconwest.

Basho

Basho Announces Technical Preview of Riak 2.0 and Riak Enterprise 2.0

San Francisco, CA – October 29, 2013 – Today at RICON West, Basho, the worldwide leader in distributed systems and cloud storage software, announced that the Technical Preview of Riak 2.0, Basho’s distributed NoSQL database, is now publicly available. This major release introduces new features that improve developer ease-of-use, increase flexibility around consistency, boost search and analytics capabilities, simplify operations at scale, and provide enterprise-class data security.

Riak continues to gain adoption worldwide supporting critical applications that require high-availability, predictable scalability, and performance. Riak’s unique ability to distribute data, both to ensure availability and provide data locality, provides enterprises a proven database technology for powering critical web, mobile and social applications, cloud computing platforms, and to store and serve machine-to-machine and sensor data. Riak is used by thousands of companies, including over 30% of the Fortune 50.

New Features in Riak 2.0

  • Riak Data Types. Riak 2.0 includes a range of flexible, distributed data types, that greatly simplify application development without sacrificing Riak’s availability and partition tolerance characteristics. Available Riak data types include distributed counters, sets, maps, registers, and flags.
  • Strong Consistency. Developers now have the flexibility to choose whether buckets should be eventually consistent (the default Riak configuration today that provides high availability) or strongly consistent, based on data requirements.
  • Full-Text Search Integration with Apache Solr. Riak Search is completely redesigned in Riak 2.0, leveraging the Apache Solr engine. Riak Search in 2.0 fully supports the Solr client query APIs, enabling integration with a wide range of existing software and commercial solutions.
  • Security. Riak 2.0 adds the ability to administer access rights and utilize plug-in authentication models. Authentication and Authorization is provided via client APIs.
  • Simplified Configuration Management. Riak 2.0 continues to improve Riak’s operational simplicity by changing how, and where, configuration information is stored in an easy-to-parse and transparent format.
  • Reduced Replicas for Secondary Sites. Exclusive to Riak Enterprise 2.0, users can now optionally store fewer copies of replicated data across multiple datacenters to better maintain a balance between storage overhead and availability.

Technical Preview Availability

Download the Riak 2.0 Technical Preview here. All code for Riak 2.0 is also available on Github. For more details on the technical preview for Riak, visit our blog.

About RICON West
RICON West 2013 is part of the RICON conference series. RICON is Basho’s distributed systems conference for developers and academics. RICON West will take place in San Francisco, CA on October 29-30. More than 25 speakers will discuss applications, use cases, and the future of distributed systems – including NoSQL solutions and cloud storage. RICON West 2013 speakers include Basho, Google, Microsoft Research, Netflix, salesforce.com, Seagate, State Farm Insurance, The Weather Company, and Twitter. RICON West 2013 is sold-out; however, Basho will offer a live stream.

About Basho
Basho is a distributed systems company dedicated to making software that is highly available, fault-tolerant and easy-to-operate at scale. Basho’s distributed database, Riak, and Basho’s cloud storage software, Riak CS, are used by fast growing Web businesses and by over 25 percent of the Fortune 50 to power their critical Web, mobile and social applications and their public and private cloud platforms.

Riak and Riak CS are available open source. Riak Enterprise and Riak CS Enterprise offer enhanced multi-datacenter replication and 24×7 Basho support. For more information, visit basho.com. Basho is headquartered in Cambridge, Massachusetts and has offices in London, San Francisco, Tokyo and Washington DC.

Introducing Riak 2.0: Data Types, Strong Consistency, Full-Text Search, and Much More

October 29, 2013

Today at RICON West in San Francisco, we announced the Technical Preview of Riak 2.0 is now available. This major release adds a number of new features that many of you have been waiting for.

Throughout RICON West, we will be discussing many of the Riak 2.0 features (both in track sessions or during lightning talks), so keep your eyes on the live stream over the next two days. Videos of all sessions will also be made available after the conference.

Here is a look at some of the major enhancements available in Riak 2.0:

  • Riak Data Types. Building on the eventually consistent counters introduced in Riak 1.4, Riak 2.0 adds sets and maps as new distributed data types. These Riak Data Types simplify application development without sacrificing Riak’s availability and partition tolerance characteristics.
  • Strong Consistency. Developers have the flexibility to choose whether buckets should be eventually consistent (the default Riak configuration today that provides high availability) or strongly consistent, based on data requirements.
  • Full-Text Search Integration with Apache Solr. Riak Search is completely redesigned in Riak 2.0, leveraging the Apache Solr engine. Riak Search in 2.0 supports the Solr client query APIs, enabling integration with a wide range of existing software and commercial solutions.
  • Security. Riak 2.0 adds the ability to administer access rights and utilize plug-in authentication models. Authentication and Authorization is provided via client APIs.
  • Simplified Configuration Management. Riak 2.0 continues to improve Riak’s operational simplicity by changing how, and where, configuration information is stored in an easy-to-parse and transparent format.
  • Reduced Replicas for Multiple Data Centers. Riak Enterprise 2.0 can optionally store fewer copies of replicated data across multiple data centers to better maintain a balance between storage overhead and availability.

Ready to get started? Download the Technical Preview.

Please note that this is only a Technical Preview of Riak 2.0. This means that it has been tested extensively, as we do with all of our release candidates, but there is still work to be completed to ensure it’s production hardened. Between now and the final release, we will be continuing manual and automated testing, creating detailed use cases, gathering performance statistics, and updating the documentation for both usage and deployment.

As we are finalizing Riak 2.0, we welcome your feedback for our Technical Preview. We are always available to discuss via the Riak Users mailing list, IRC (#riak on freenode), or contact us.

Riak 2.0 Technical Preview: Deep Dive

Riak Data Types
In distributed systems, we are forced to trade consistency for availability (see: CAP Theorem) and this can complicate some aspects of application design. In Riak 2.0, we have integrated cutting-edge research on data types known as called CRDTs (Conflict-Free Replicated Data Types) pioneered by INRIA to create Riak Data Types. By adding counters, sets, maps, registers, and flags, these Riak Data Types enable developers to spend less time thinking about the complexities of vector clocks and sibling resolution and, instead, focusing on using familiar, distributed data types to support their applications’ data access patterns.

A more detailed overview of Riak Data Types is available that examines implementation considerations and the basics of usage.

Strong Consistency
In all prior versions, Riak was classified as an eventually consistent system. With the 2.0 release, Riak now lets developers choose when operations should be strongly or eventually consistent. This gives developers a choice between these semantics for different types of data. At the same time, operators can continue to enjoy the operational simplicity of Riak. Consistency preferences are defined on a per bucket type basis, in the same cluster.

A RICON West 2012 talk entitled, Bringing Consistency to Riak, shares much of the initial thinking behind this effort. In addition, the pull request that adds consistency to riak_kv provides detailed information about related repositories and the implementation approach.

Redesigned Full-Text Search
Riak is a key/value store and the values are simply stored on disk as binary. With previous versions of Riak Search, Riak developers have long been able to index the content of these stored values. In Riak 2.0, Riak Search (code-named Yokozuna) has been completely redesigned and now uses the Apache Solr full-text document indexing engine directly. Together, Riak and Solr provide a reliable full-text context indexing solution that is highly available and built for scale. In addition, Riak Search 2.0 also fully supports the Solr client query APIs, which enables integration with existing software solutions (either homegrown or commercial).

The Basho engineers responsible for Yokozuna have created a resources page that includes recorded talks, Solr documentation links, and books on the topic.

Security
Basho designed Riak with critical data in mind. Whether it’s data that affects revenue, user experience, or even a patient’s health (as is the case with the NHS), Riak ensures that this critical data is always available. However, often this critical data is also sensitive data. Riak 2.0 adds security to this data through the ability to administer access rights and plug-in various secure authentication models commonly used today.

The initial RFC that describes the security effort, including related Pull Requests, is available at github.com/basho/riak/issues/355.

Simplified Configuration Management
At Basho, we pride ourselves on providing operationally friendly software that functions smoothly when dealing with the challenges of a distributed system. In the past, configuration of Riak occurred in two files: app.config and vm.args. Riak 2.0 changes how and where configuration information is stored. It no longer uses Erlang-specific syntax but, rather, provides a layout more suited for all operators and automated deployment tools. This layout is easy to parse and transparent for Riak administrators.

More information on the vision and specific implementation considerations are contained in the repository at github.com/basho/cuttlefish.

Bucket Types
In versions of Riak prior to 2.0, keys were made up of two parts: the bucket they belong to and a unique identifier within that bucket. Buckets act as a namespace and allow for similar keys to be grouped. In addition, they provide a means of configuring how previous versions of Riak treated that data.

In Riak 2.0, several new features (security and strong consistency in particular) need to interact with groups of buckets. To this end, Riak 2.0 includes the concept of a Bucket Type. In addition to allowing new features without special prefixes in Bucket names, Riak developers and operators are able to define a group of buckets that share the same properties and only store information about each Bucket Type, rather than individual buckets.

More information about Bucket Types can be found in the Github Issue at github.com/basho/riak/issues/362. This issue describes the planned functionality, discussions about implementation, and includes related pull requests.

Change in Defaults for Sibling Resolution
Riak has always supported both application-side and timestamp and vector clock-based Last Write Wins server-side resolution. Prior to Riak 2.0, vector clock-based Last Write Wins has been the default. Moving forward, new clusters will hand off siblings to applications by default. This is the safest way to work with Riak, but requires developers to be aware of sibling resolution.

In a blog series entitled, Understanding Riak’s Configurable Behaviours, Basho Evangelist John Daily discusses the configuration of Last Write Wins, and many other options, in great detail.

More Efficient Use of Physical Memory
Riak nodes are designed to manage the changing demands of a cluster as it experiences network, hardware, and other failures. To do this, Riak balances each node’s resources accordingly. Riak 2.0 has vastly improved LevelDB’s use of available physical memory (RAM) by allowing local databases to dynamically change their cache sizes as the cluster fluctuates under load.

In the past, it was necessary to specify RAM allocation for different LevelDB caches independently. This is no longer the case. In Riak 2.0, LevelDB databases that manage key/value or active anti-entropy data share a single pool of memory, and administrators are free to allocate as much of the available RAM to LevelDB as they feel is appropriate in their deployment. Detailed implementation documentation can be found in the basho/leveldb wiki.

Riak Ruby Vagrant Project
If you are interested in testing Riak 2.0, in a contained environment with the Riak Ruby Client, Basho engineer Bryce Kerley has put together the Riak-Ruby-Vagrant repository. In addition, this environment can be easily adapted to usage with other clients for testing the new features of Riak 2.0.

Basho