Getting Started with NoSQL « myNoSQL Couple of weeks ago, I had the pleasure to sit down with Mathias Meyer, Chief Visionary at Scalarium, a Berlin startup and discuss NoSQL adoption. Like myself, Mathias is really excited about NoSQL and he uses every opportunity to introduce more people to the NoSQL space. Recently he gave quite a few presentations around the Europe about NoSQL databases. The discussion has focused on how would someone start learning and using NoSQL databases and the path to follow in this new ecosystem. Below is a transcript of our conversation. Alex: How does one get started with NoSQL? Mathias: Well, that’s a question I get quite a lot, but it is not that easy to answer. From a business perspective, you are probably going to find some use cases where storing your data in a relational database doesn’t make too much sense and you’ll start looking for ways to get it out of the database. Alex: So, as a developer you should just give yourself a chance to play with the new shiny toys. Mathias: Indeed.
Code Monkeyism | The Blog for Developers by Stephan Schmidt Hadoop Has Promise but Also Problems... Show Me the Cheaper or Simpler Alternatives Jessica E. Vascellaro for WSJ: But some early adopters of Hadoop now say using the technology is challenging and rolling it out will take time.[…]Mr. Boroditsky says Hadoop is “immature” and comes with additional costs of hiring in-house expertise and consultants. “There is a very substantial cost to free software,” he says, declining to comment on dollar figures. I’m starting to believe that the “Hadoop has problems and is complex” chorus is a vendor reaction very similar to the reaction they had to open source in general. how many other tools can lead you to the same solution? It would be great if Hadoop administration would get simpler and operational costs would go down and if know-how would be easier to find. Original title and link: Hadoop Has Promise but Also Problems… Show Me the Cheaper or Simpler Alternatives (NoSQL database©myNoSQL)
Reflections on the New Database Revolution | The Database Revolution The recent Bloor Group roundtable discussion on The New Database Revolution covered a lot of ground. Both the benefits and challenges of the new database paradigms were discussed and a broad range of questions were raised by the audience. In thinking about how the discussion went, there are a number of themes that are worth further mention. The Need for History One important theme is the need to understand how we got where we are today. Today, we find architectures in enterprises that cannot be explained by conscious decisions based on a single current architecture. So we have an existing architecture, which is already very complex and may not be fully understood (or understandable) and we are going to have to add to it to support the new database platforms. Before and After the Relational Interlude Another historical topic that came up in the roundtable was the existence of databases in the long-forgotten world prior to the dominance of the relational paradigm.
SOA Patterns - Partial State Deferral How can services be designed to optimize resource consumption while still remaining stateful? Problem Service capabilities may be required to store and manage large amounts of state data, resulting in increased memory consumption and reduced scalability. Solution Even when services are required to remain stateful, a subset of their state data can be temporarily deferred. Application Various state management deferral options exist, depending on the surrounding architecture. Impacts Partial state management deferral can add to design complexity and bind a service to the architecture. Architecture Inventory, Service Applying this pattern results in the same amount of concurrent service instances but less overall state-related memory consumption.
ApplicationDatabase application integration · database tags: I use the term Application Database for a database that is controlled and accessed by a single application, (in contrast to an IntegrationDatabase). Since only a single application accesses the database, the database can be defined specifically to make that one application's needs easy to satisfy. This leads to a more concrete schema that is usually easier to understand and often less complex than that for an IntegrationDatabase. To share data with other applications the controlling application may provide services. One the great advantages of an application database is that it is easier to change since all its use is encapsulated by a single application. An application database schema is usually best designed and controlled by the application team themselves - often by having an experienced database professional as a member of the application team.
DatabaseThaw database · noSQL tags: A few years ago I heard programming language people talk about the "Nuclear Winter" in languages caused by Java. Tim Bray's thought-provoking keynote talked about storage; including highlighting several alternatives to the conventional database world When I started in the software development profession, I worked with several people who had evangelized relational databases. At QCon last week, there was a strong thread of talks that questioned this assumption. As well as this talk, there was a whole track on alternative databases hosted by Kresten Krab Thorup. The natural question to ask about these products is why they should prevail when the ODBMSs failed. Kresten Krab Thorup does a great job as a leader of the technical content of the JAOO and QCon conferences. For many organizations today, the primary pattern for integration is Shared Database Integration - where multiple applications are integrated by all using a common database.
Top Differences between OAuth 1.0 and OAuth 2.0 for API Calls OAuth 1.0 (the current spec version is 1.0a, which fixes a security problem with 1.0) solves an important problem in the world of APIs -- how one web application can give another application API access without requiring that the user give out their password. OAuth 1.0 solves this problem in a clever way through a secure handshake, via API calls, between the two applications. This has allowed APIs to go in places where they could never go before. OAuth 1.0 works by ensuring that the API client and server share a token, which is like a username, and a token secret, which is like a password. The advantage of this approach is that there is no way to find out the token secret, because it is always encrypted when it's sent over the network, and only the client and server have the keys. However, both client and server developers found the complexity of generating and validating signatures to be too much. OAuth 2.0 promises to simplify this stuff in a number of ways: 1. Spec changes.
Architecture & Design Content on InfoQ Research on Architecture & Design What Scares You Most About Adopting a Microservice Architecture? Microservices solve all architectural problems - or do they? Which of the many challenges of a microservice architecture worries you most? What's Your Next Native Language? What native languages do you use if neither the JVM, .NET VM or JS VM is available or wanted? How Do You Unit Test Your JavaScript Code? Recently, we asked you about your JavaScript testing approaches, and your responses showed Unit Testing Tools as the most popular. What IoT Technology Have You Used or Learned About? InfoQ Research wants to determine the technologies mostly used by our community in their IoT projects. What is Your Interest in the IoT? InfoQ wants to evaluate the involvement of our community in hobbyist or real-life IoT projects.
July 2012 We have found that the best defense against major unexpected failures is to fail often. By frequently causing failures, we force our services to be built in a way that is more resilient. We are excited to make a long-awaited announcement today that will help others who embrace this approach. Do you think your applications can handle a troop of mischievous monkeys loose in your infrastructure? What is Chaos Monkey? Chaos Monkey is a service which runs in the Amazon Web Services (AWS) that seeks out Auto Scaling Groups (ASGs) and terminates instances (virtual machines) per group. Why Run Chaos Monkey? Failures happen and they inevitably happen when least desired or expected. There are many failure scenarios that Chaos Monkey helps us detect. Auto Scaling Groups The default instance groupings that Chaos uses for selection is Amazon's Auto Scaling Group (ASG). Configuration Chaos Monkey allows for an Opt-In or an Opt-Out model. Costs More Monkey Business
“cloud architecture” At Netflix we work hard to improve personalized recommendations. We use a lot of data to make recommendations better. What may seem an arbitrary action -- scrolling up, down, left or right and how much -- actually provides us with valuable information. It is obvious that to capture the large amount of data generated, we need a dedicated, fast, scalable and highly available and asynchronous collection system that does not slow the user experience. In this post we discuss the decisions and considerations that went into building a service that accepts a few billion requests a day, processing and storing these requests for later use and analysis by various systems within Netflix. Considerations We did not want this service to disrupt the user experience, hence, the main objective was as low a latency as possible. Data Size The average size of the request and the logged data is around 16 KB (range: 800 bytes ~ 130 KB) whereas the response average is pretty consistent at around 512 bytes.
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