With unstructured database technologies like Cassandra, MongoDB and even JSON storage in Postgres, unstructured data has become remarkably easy to store and to process. Software and data engineers alike can succeed in a world (mostly) free from data modelling, which is no longer a prerequisite to collecting data or extracting value from it.
NoSQL databases have been around for several years and have become a preferred choice for managing unstructured data. InfoQ spoke with four panelists about the current state of NoSQL databases. 2
Datastax recently announced DataStax Graph to support graph data models. InfoQ spoke with Martin Van Ryswyk from DataStax team about the new product. 1
ColumnarStore can offer performance improvements over traditional tables, but aren’t always faster. Aleksandr Shavlyuga explores the power, and limitations of SQL Server’s ColumnStore Indexes.
NoSQL for Mere Mortals introduces the major types of databases that fall under the NoSQL umbrella and explains both their advantages and shortcomings. Review and interview with the author. 2
Practical Cassandra: A Developer's Approach book is a developer's guide to build applications using Cassandra NoSQL database. InfoQ spoke with authors about the book and data modeling in Cassandra.
Jon Natkins explains in this article how to create a personalized recommendation system fed with large amounts of real-time data using Kiji, which leverages HBase, Avro, Map-Reduce and Scalding.
In this article, Boris Lublinsky shows how to extend Hbase - based Lucene implementation with geospatial search support.
In this article, authors, Boris Lublinsky and Mike Segel suggest an approach for using HBase as a scalable back end for Lucene Search. 3