Which freaking database should I use? August 02, 2012 Follow @acoliver I've been in Chicago for the last few weeks setting up our first satellite office for my company.
While Silicon Valley may be the home of big data vendors, Chicago is the home of the big data users and practitioners. So many people here "get it" that you could go to a packed meetup or big data event nearly every day of the week. Big data events almost inevitably offer an introduction to NoSQL and why you can't just keep everything in an RDBMS anymore. . [ Andrew Oliver declares the time for NoSQL standards is now. | Also on InfoWorld: NoSQL standouts: New databases for new applications | Get a digest of the key stories each day in the InfoWorld Daily newsletter. ] Part of the reason there are so many different types of NoSQL databases lies in the CAP theorem, aka Brewer's Theorem. 5 Graph Databases to Consider. Of the major categories of NoSQL databases - document-oriented databases, key-value stores and graph databases - we've given the least attention to graph databases on this blog.
That's a shame, because as many have pointed out it may become the most significant category. Graph databases apply graph theory to the storage of information about the relationships between entries. The relationships between people in social networks is the most obvious example. The relationships between items and attributes in recommendation engines is another. OpenRDF.org: Home.
Giraph - Welcome To Apache Giraph! Emmet Documentation. SymPy. JPype - Java to Python integration. TinkerPop. Weka 3 - Data Mining with Open Source Machine Learning Software in Java. RStudio IDE. PyLab - Currently this page reflects the vision of KeirMierle , and not necessarily the community as a whole.
By integrating consensus from mailing list discussions, I will refine and polish this vision and form a plan of action such that the community can move the numpy+scipy+ipython+matplotlib ensemble closer to the vision outlined below. See the following post for further discussion of the difference between the vision for a new PyLab expressed on this page, and the existing pylab package which is part of matplotlib: To make PyLab an easy to use, well packaged, well integrated, and well documented, numeric computation environment so compelling that instead of having people go to Python and discovering that it is suitable for numeric computation, The philosophy behind this vision is to consider Rails and Ruby; while Ruby was somewhat popular beforehand, it was Rails which propelled it to the forefront.
Short-term Goals A simple user story. Scalalab - A Matlab like environment for Scala. Since Google disabled creating new downloads, new downloads can be available from: ScalaLab is migrated with Google's automatic exporter to Github: Project Summary The ScalaLab project aims to provide an efficient scientific programming environment for the Java Virtual Machine.
The scripting language is based on the Scala programming language enhanced with high level scientific operators and with an integrated environment that provides a MATLAB-like working style. Also, all the huge libraries of Java scientific code can be easily accessible (and many times with a more convenient syntax). The MATLAB-like mathematical DSL of ScalaLab is termed ScalaSci , and is developed as an internal DSL, by exploiting the superb extensibility of the Scala language. Toolboxes of Java scientific code can be easily installed, using a menu based installation procedure.
Many environment configuration options can be easily performed within the graphical user interface. Installation 1. 2. Ant. Home - jHepWork. Freedom to choose a programming language. Freedom to choose an operating system. Freedom to share your code. Enjoy the freedom of SCaVis. List of Unified Modeling Language tools. UML, BPMN and Enterprise Architecture Tool for Software Development. Software Ideas Modeler (v.5.84) - Setup - Software Ideas Modeler - Free & Powerful CASE Tool with UML Support.
Violet UML Editor : easy to use, completely free. OrientDB Graph-Document NoSQL dbms. Titan. Titan is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster.
Titan is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time. In addition, Titan provides the following features: Download Titan or clone from GitHub. Read the Titan documentation and join the mailing list. <dependency><groupId>com.thinkaurelius.titan</groupId><artifactId>titan-core</artifactId><version>1.0.0</version></dependency><!
Announcements — IPython. Network Analysis And Visualization. The Diagramming Company. Navigator Sales. Graphviz - Graph Visualization Software. Overview — NetworkX. Graph_survey - Sage Wiki. Introduction.
Natural Language Toolkit — NLTK 2.0 documentation. Mathics - A free, light-weight alternative to Mathematica. Sage - Tour. Sage is built out of nearly 100 open-source packages and features a unified interface.
Sage can be used to study elementary and advanced, pure and applied mathematics. This includes a huge range of mathematics, including basic algebra, calculus, elementary to very advanced number theory, cryptography, numerical computation, commutative algebra, group theory, combinatorics, graph theory, exact linear algebra and much more.