One feature of the big data revolution is the acknowledgement that a single database management system architecture cannot meet all needs. However, the Lambda Architecture provides a useful pattern for combining multiple big data technologies to achieve multiple enterprise objectives. First proposed by Nathan Marz, it attempts to provide a combination of technologies that together can provide the characteristics of a web-scale system that can satisfy requirements for availability, maintainability, and fault-tolerance.
Posted October 08, 2014
Not all Hadoop packages offer a unique distribution of the Hadoop core, but all attempt to offer a differentiated value proposition through additional software utilities, hardware, or cloud packaging. Against that backdrop, Intel's distribution of Hadoop might appear to be an odd duck since Intel is not in the habit of offering software frameworks, and the brand, while ubiquitous, is not associated specifically with Hadoop, databases or big data software. However, given its excellent partnerships across the computer industry, Intel has support from a variety of vendors, including Oracle and SAP, and many of the innovations in its distribution show real promise.
Posted December 04, 2013
Security for NoSQL continues to evolve rapidly in order to attract wider enterprise adoption. Robust security is a must-have for any database in the enterprise, and over the decades since the emergence of the relational model, security and authentication capabilities have continually improved. The first new-generation non-relational "NoSQL" databases, like the early relational databases, had very simplistic security mechanisms. Here is how security for NoSQL is changing.
Posted October 09, 2013
In many ways, Hadoop is the most concrete technology underlying today's big data revolution, but it certainly does not satisfy those who want quick answers from their big data. Hadoop - at least Hadoop 1.0 - is a batch-oriented framework that allows for the economical execution of massively parallel workloads, but provides no capabilities for interactive or real-time execution.
Posted August 07, 2013
When NoSQL first hit the IT consciousness in 2009, an explosion of NoSQL databases seemed to appear out of thin air. Some of these contenders had in fact been around for some time, with others thrown together rather quickly to exploit the NoSQL buzz. The NoSQL pack thinned out as leaders in specific categories emerged, but for some time, there was no clear leading key-value NoSQL database.
Posted June 13, 2013
The term "NoSQL" is widely acknowledged as an unfortunate and inaccurate tag for the non-relational databases that have emerged in the past five years. The databases that are associated with the NoSQL label have a wide variety of characteristics, but most reject the strict transactions and stringent relational model that are explicitly part of the relational design. The ACID (Atomic-Consistent-Independent-Durable) transactions of the relational model make it virtually impossible to scale across data centers while maintaining high availability, and the fixed schemas defined by the relational model are often inappropriate in today's world of unstructured and rapidly mutating data.
Posted April 10, 2013
Hadoop is the most significant concrete technology behind the so called "Big Data" revolution. Hadoop combines an economical model for storing massive quantities of data - the Hadoop Distributed File System - with a flexible model for programming massively scalable programs - MapReduce. However, as powerful and flexible as MapReduce might be, it is hardly a productive programming model. Programming in MapReduce reminds one of programming in Assembly language - the simplest operations require substantial code.
Posted February 13, 2013
As the undisputed pioneer of big data, Google established most of the key technologies underlying Hadoop and many of the NoSQL databases. The Google File System (GFS) allowed clusters of commodity servers to present their internal disk storage as a unified file system and inspired the Hadoop Distributed File System (HDFS). Google's column-oriented key value store BigTable influenced many NoSQL systems such as Apache HBase, Cassandra and HyperTable. And, of course, the Google Map-Reduce algorithm became the foundation computing model for Hadoop and was widely implemented in other NoSQL systems such as MongoDB.
Posted December 06, 2012
Google is the pioneer of big data. Technologies such as Google File System (GFS), BigTable and MapReduce formed the basis for open source Hadoop, which, more than any other technology, has brought big data within reach of the modern enterprise.
Posted October 10, 2012
Throughout the 2000s, a huge number of website developers rejected the Enterprise Java or .NET platforms for web development in favor of the "LAMP" stack - Linux, Apache, MySQL and Perl/Python/PHP. Although the LAMP stack was arguably less scalable or powerful than the Java or .NET frameworks, it was typically easier to learn, faster in early stages of development - and definitely cheaper. When enterprise architects designed systems, they often chose commercial application servers and databases (Oracle, Microsoft, IBM). But, when web developers or startups faced these decisions, the LAMP stack was often the default choice.
Posted August 09, 2012
One of the earliest of the new generation of non-relational databases was CouchDB. CouchDB was born in 2005 when former Lotus Notes developer Damien Katz foresaw the nonrelational wave that only fully arrived in 2009. Katz imagined a database that was fully compatible with web architectures — and more than a little influenced by Lotus Notes document database concepts.
Posted June 13, 2012
It's hard to overestimate Amazon's influence on cloud computing and on NoSQL databases. Amazon Web Services (AWS) was the first and still is the leading concrete example of an infrastructure as a service (IaaS) cloud - a collection of cloud-based services such as compute (EC2), storage (S3) and other application building blocks.
Posted April 11, 2012
In years to come, we might remember October 2011 as the month the big database vendors gave in to the dark side and embraced Hadoop. In October, both Microsoft and Oracle announced product offerings which included and embraced Hadoop as the enabler of their "big data" solution. The last of the big three database vendors - IBM - embraced Hadoop back in 2010.
Posted February 09, 2012
As the leading provider of relational database software, it's hardly surprising that Oracle initially gave little or no credence to the NoSQL movement that emerged in 2009. Indeed, an Oracle white paper from May 2011 concluded with the recommendation to "Go for the tried and true path," and avoid NoSQL databases.
Posted December 01, 2011
One of the greatest achievements in artificial intelligence occurred earlier this year when IBM's Watson supercomputer defeated the two reigning human champions in the popular Jeopardy! TV show. Named after the IBM founder Thomas Watson and not - as you may have thought - Sherlock Holmes' famous assistant, Watson was the result of almost 5 years of intensive effort by IBM, and the intellectual successor to "Deep Blue," the first computer to beat a chess grand master.
Posted October 15, 2011
Michael Stonebraker is widely recognized as one of the pioneers of the relational database. While at Berkeley, he co-founded the INGRES project, which implemented the relational principles published by Edgar Codd in his seminal papers. The INGRES project became the basis for the commercial Ingres RDBMS, which, during the 1980s, provided some of the most significant competition to Oracle.
Posted August 11, 2011
Both HBase and Cassandra can deal with large data sets, and provide high transaction rates and low latency lookups. Both allow map-reduce processing to be run against the database when aggregation or parallel processing is required. Why then, would a merge of Cassandra and Hadoop be a superior solution?
Posted June 08, 2011
The relational database is primarily oriented toward the modeling of objects (entities) and relationships. Generally, the relational model works best when there are a relatively small and static number of relationships between objects. It has long been a tricky problem in the RDBMS to work with dynamic, recursive or complex relationships. For instance, it's a fairly ordinary business requirement to print out all the parts that make up a product - including parts which, themselves, are made up of smaller parts. However, this "explosion of parts" is not consistently supported by all the relational databases. Oracle, SQL Server and DB2 have special, but inconsistent, syntax for these hierarchical queries, while MySQL and PostgreSQL lack specific support.
Posted April 05, 2011
Salesforce.com is well known as the pioneer of software as a service (SaaS) - the provision of hosted applications across the internet. Salesforce launched its SaaS CRM (Customer Relationship Management) product more than 10 years ago, and today claims over 70,000 customers. It's less widely known that Salesforce.com also has been a pioneer in platform as a service (PaaS), and is one of the first to provide a comprehensive internet-based application development stack. In 2007 - way before the current buzz over cloud development platforms such as Microsoft Azure - Salesforce launched the Force.com platform, which allowed developers to run applications on the same multi-tenant architecture that hosts the Salesforce.com CRM.
Posted February 02, 2011
Because any database that does not support the SQL language is, by definition, a "NoSQL" database, some very different databases coexist under the NoSQL banner. Massively scalable data stores like Cassandra, Voldemort, and HBase sacrifice structure to achieve scale-out performance. However, the document-oriented NoSQL databases have very different architectures and objectives.
Posted November 30, 2010
In Greek mythology, Cassandra was granted the gift of prophesy, but cursed with an inability to convince others of her predictions - a sort of unbelievable "oracle," if you like. Ironically, in the database world, the Cassandra system is fast becoming one of the most credible non-relational databases for production use - a believable alternative to Oracle and other relational databases.
Posted October 12, 2010
NoSQL - probably the hottest term in database technology today - was unheard of only a year ago. And yet, today, there are literally dozens of database systems described as "NoSQL." How did all of this happen so quickly? Although the term "NoSQL" is barely a year old, in reality, most of the databases described as NoSQL have been around a lot longer than the term itself. Many databases described as NoSQL arose over the past few years as reactions to strains placed on traditional relational databases by two other significant trends affecting our industry: big data and cloud computing.
Posted August 10, 2010