A Comparison Of NoSQL Database Management Systems And Models A previous version of this article was written by O.S. Tezer. Introduction When most people think of a database, they often envision the traditional relational database model that involves tables made up of rows and columns. While relational database management systems still handle the lion’s share of data on the internet, alternative data models have become more common in recent years as developers have sought workarounds to the relational model’s limitations. This article will introduce you to a few of the more commonly used NoSQL database models. Relational Databases and Their Limitations Databases are logically modeled clusters of information, or data. All database management systems have an underlying model that structures how data is stored and accessed. Historically, the relational model has been the most widely used approach for managing data, and to this day many of the most popular database management systems implement the relational model. About NoSQL Key-value Databases
Cassandra vs MongoDB vs CouchDB vs Redis vs Riak vs HBase vs Couchbase vs Hypertable vs ElasticSearch vs Accumulo vs VoltDB vs Scalaris comparison :: Software architect Kristof Kovacs While SQL databases are insanely useful tools, their monopoly in the last decades is coming to an end. And it's just time: I can't even count the things that were forced into relational databases, but never really fitted them. (That being said, relational databases will always be the best for the stuff that has relations.) But, the differences between NoSQL databases are much bigger than ever was between one SQL database and another. In this light, here is a comparison of Open Source NOSQL databases: The most popular ones # Redis # Best used: For rapidly changing data with a foreseeable database size (should fit mostly in memory). For example: To store real-time stock prices. Cassandra # Written in: JavaMain point: Store huge datasets in "almost" SQLLicense: ApacheProtocol: CQL3 & ThriftCQL3 is very similar to SQL, but with some limitations that come from the scalability (most notably: no JOINs, no aggregate functions.)CQL3 is now the official interface. MongoDB # ElasticSearch # CouchDB #
Thoughts on development using CouchDB with Node.js | Tim Branyen @tbranyen I was recently on a client facing project for Bocoup and needed to store millions of tweets that contained sentiment analysis of the text. From this sentiment gathered along with other various metadata, I was tasked with creating a scalable API that could query/filter the data retrieved. This post will discuss the Why and the How behind my first experience with CouchDB and how I created a better development environment in order to deliver a polished product. Why CouchDB? First and foremost, I have a "background" with MySQL, SQLite and SQL Server from previous employment and college. I had very simple requirements: Easily put data into the store && easily get data out of the store. I made the decision for CouchDB after having conversations with peers and feeling comfortable that I could complete this project with: The abundant support via the communityThe rich feature set for queryingThe local cluster hosting provider Cloudant Community The easiest sell for CouchDB, to me, was the community.
Add search features to your application, try Elasticsearch part 3 : attaching indexation to events « Diving deep into JEE Now that we are able to index, we should think of when whe should trigger indexing tasks. A simple answer would be : whenever some indexed data has changed. “Changed” means change cardinality (add/remove) or change existing data. Either we invoke indexing tasks whenever we code an action that changes data or we use an event model which listens to precise events. 1 – JPA event model If you use JPA as a persistence mechanism you can take advantage of its elegant mechanism. Below, an example: That model, although very elegant, doesn’t suit you if you use Spring because the persistence can’t use a bean instance. 2 – Hibernate event model When using Hibernate, without JPA, with Spring you can register instances, not only classes. PostCommitDeleteEventListener source code: This is one of the most non intrusive solution. 3 – Spring event model When you’re stuck with JPA you can use Spring event model. Example of ApplicationEventPublisher call: Example of event listener: 4 – Elasticsearch river
Building a Real-time SMS Voting App: Scaling Node.js and CouchDB This tutorial uses the Twilio Node.JS Module and the Twilio Rest Message API This is the third in a multi-part series of blog posts on building a real-time SMS and voice voting application using Node.js. In part one, we created the Node.js application and captured incoming votes over SMS. In part two, we created a real-time visualization of the voting using Socket.io. At the end of part two of this blog post series, I mentioned that while we had a working SMS voting app with a cool real-time visualization, it was not a solution that was going to scale. You’ll notice that information about the event (it’s name, etc) and all of the votes for that event are contained within the same document. If many votes arrived rapidly, our app as currently written will quickly fail. Well, one solution is to decouple event data from vote data. Modeling one-to-many relationships In a SQL database, modelling one-to-many relationships is trivial. We have added a type attribute. What’s going on here?
Accéder à une base CouchDB via l'interface REST Ça y est? Vous avez installé CouchDB? Il est temps maintenant de s'en servir! Dans cet article, nous allons aborder les concepts de base et voir comment accéder à une base CouchDB via l'interface REST. REST – pour Representational State Transfer – est une architecture client-serveur dans laquelle un client utilise le vocabulaire standard d'un protocole pour identifier et manipuler des ressources sur un serveur. Un point clé étant que le serveur est sans état. Le cas d'école pour l'architecture REST est l'utilisation du protocole HTTP. Heu... Oui, d'accord, ça n'est qu'une introduction très superficielle à l'architecture REST. (en) Leonard Richardson, Sam Ruby. Pour en revenir au sujet de cet article, CouchDB expose une API (Application Programming Interface – L'ensemble des spécifications de classes, méthodes, fonctions, constantes, etc. qui permettent d'utiliser une technologie dans un programme.) Note: Pour commencer Installation Donc, CouchDB est installé sur votre machine. Oups!
ie - Very fast web app development Complete! We're on it Planned Offline by default: Hoodie stores data locally first and syncs them in the background when possible. Great for mobile applications One-line signup/signin/signout/resend password and other account management functions Document-based storage with CouchDB: no building database schemas Event system: easily listen for changes in the data to trigger view updates JavaScript and JSON on every layer. Even the database queries are JS Convenient, super simple local dev setup that optionally even configures .dev-domains for you Deploy to Nodejitsu with minimal effort Flexible, npm-based plugin system in case you need more capability Send multi-part emails with attachments from the client Powerful, fine-grained sharing settings for even the tiniest piece of data Receive payments from your users Authenticate with other services (Twitter, GitHub, etc.) Hoodie hosting for even simpler deployment Remove jQuery dependency For you! So how simple is Hoodie? 1. 2. 3. 4. 5. Store
Unconventional architectures that might scale (I) | log4p I’m experimenting with some unconventional architectural ideas (at least from a Java developers view) while designing a new architecture for Dutch broadcaster VPRO. In this series of blogposts I’ll try to explain some of the concepts; please feel free to point out issues/caveats I failed to notice! Some aims of the architecture ReliablePerformant & Scalable (VPRO is running high traffic sites like 3voor12 and cinema.nl)Language agnostic frontend (and preferably backend)Web OrientedMaintainableOffers option to create new concepts and deliver to yet unknown platform with existing content Conceptually I would like to solve this by creating ‘services’ (no, not talking about ‘classical’ SOA here) around specific domains. On top of that a REST/HTTP based layer would be created to provide the necessary API on which websites, widgets or mobile applications can be build. Proof-of-Concept implementation based on CouchDB CouchDB offers a JSON based document model. class CouchDBAccessorService { [php]