InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
-
/articles/data-analytics-center-of-excellence/en/smallimage/logo.jpg)
Cindy Walker on Data Management Best Practices and Data Analytics Center of Excellence
Cindy Walker spoke at Enterprise Data World Conference about using semantic approaches to augment the data management practices. InfoQ spoke with her about the data management best practices and the data analytics center of excellence initiative.
-
/articles/data-modeling-with-key-value-nosql-data-stores/en/smallimage/logo2.jpg)
Data Modeling with Key Value NoSQL Data Stores – Interview with Casey Rosenthal
In Key Value data stores, data is represented as a collection of key–value pairs. The key–value model is one of the simplest non-trivial data models, and richer data models are implemented on top of it. InfoQ spoke with Casey Rosenthal from Basho team about the data modeling concepts and best practices when using these NoSQL databases for data management.
-
/articles/rich-reimer-splice-machine/en/smallimage/splice-machine-logo.jpg)
Rich Reimer on SQL-on-Hadoop Databases and Splice Machine
SQL-on-Hadoop technologies include a SQL layer or a SQL database over Hadoop. These solutions are becoming popular recently as they solve the data management issues of Hadoop and provide a scale-out alternative for traditional RDBMSs. InfoQ spoke with Rich Reimer, VP of Marketing and Product Management at Splice Machine about the architecture and data patterns for SQL in Hadoop databases.
-
/articles/MarkLogic-NoSQL-with-Transactions/en/smallimage/logo.jpg)
Transactional NoSQL Database
Document-oriented NoSQL databases are eliminating the impedance mismatch between developers and traditional data models. However developers have come to believe they need to sacrifice ACID transactions. In this article we will look at how MarkLogic dispels this myth
-
/articles/apache-kafka/en/smallimage/logo.png)
Apache Kafka: Next Generation Distributed Messaging System
Apache Kafka is a distributed publish-subscribe messaging system. This article covers the architecture model, features and characteristics of Kafka framework and how it compares with traditional messaging systems.
-
/articles/data-modeling-graph-databases/en/smallimage/graph-logo.png)
Data Modeling in Graph Databases: Interview with Jim Webber and Ian Robinson
Data modeling with Graph databases requires a different paradigm than modeling in Relational or other NoSQL databases like Document databases, Key Value data stores, or Column Family databases. InfoQ spoke with Jim Webber and Ian Robinson about data modeling efforts when using Graph databases.
-
/articles/mlconf-nyc-2014-highlights/en/smallimage/logo.jpg)
MLConf NYC 2014 Highlights
The MLConf conference was going strong in NYC on April 11th and was a full day packed with talks around Machine Learning and Big Data, featuring speakers from many prominent companies.
-
/articles/nosql-time-series-data-management/en/smallimage/time-series-article-logo2.png)
NoSQL, JSON, and Time Series Data Management: Interview with Anuj Sahni
Time series data management is gaining more attention lately because the data is coming at us from all directions: sensors, mobile devices, Web tracking, financial events, factory automation, and utilities. InfoQ spoke with Anuj Sahni, Principal Product Manager at Oracle about the time series data and how to do data modeling for this type of data.
-
/articles/SQL-Server-2014-NoSQL/en/smallimage/Logo.png)
SQL Server 2014: NoSQL Speeds with Relational Capabilities
For the last four years Microsoft has been working on the first rewrite of SQL Server’s query execution since 1998. The goal is to offer NoSQL-like speeds without sacrificing the capabilities of a relational database. At the heart of this is Hekaton, their memory optimized tables. While still accessible via traditional T-SQL operations, internally they are a fundamentally different technology.
-
/articles/lambda-architecture-scalable-big-data-solutions/en/smallimage/logo.png)
Lambda Architecture: Design Simpler, Resilient, Maintainable and Scalable Big Data Solutions
Lambda Architecture proposes a simpler, elegant paradigm designed to store and process large amounts of data. In this article, author Daniel Jebaraj presents the motivation behind the Lambda Architecture, reviews its structure with the help of a sample Java application.
-
/articles/embedded-analytics-and-statistics-for-big-data/en/smallimage/logo.jpg)
Embedded Analytics and Statistics for Big Data
This article provides an overview of tools and libraries available for embedded data analytics and statistics, both stand-alone software packages and programming languages with statistical capabilities. The authors also discuss how to combine and integrate these embedded analytics technologies to handle big data.
-
/articles/bigdata-analytics-for-security/en/smallimage/logo.png)
Big Data Analytics for Security
In this article, authors discuss the role of big data and Hadoop in security analytics space and how to use MapReduce to efficiently process data for security analysis for use cases like Security Information and Event Management (SIEM) and Fraud Detection.