Tag: Cassandra

Feed: Percona Database Performance Blog. Author: Colin Charles. Colin Charles  | September 15, 2017 |  Posted In: Database Poll, MongoDB, MySQL PREVIOUS POST In this blog post, we talk about the results of Percona’s time series database poll “What Database Engine Are You Using to Store Time Series Data?” Time series data is some of the most actionable data available when it comes to analyzing trends and making predictions. Simply put, time series data is data that is indexed not just by value, but by time as well – allowing you to view value changes over time as they occur. Obvious uses include ... Read More

Feed: Hortonworks Blog – Hortonworks. Author: Will Xu. As more and more workloads are being brought onto modern hardware in the cloud, it’s important for us to understand how to pick the best databases that can leverage the best hardware. Amazon has introduced instances with directly attached SSD (Solid state drive). Both Apache HBase and Apache Cassandra are popular key-value databases. In this benchmark, we hope to learn more about how they leverage the directly attached SSD in a cloud environment. The benchmark is designed for running Apache HBase and Apache Cassandra in an optimal production environment. This means using ... Read More

Feed: Blue Medora. Author: bluemedora_editor. “Digital transformation”–the mantra of the modern enterprise–drives dramatic changes in development and digital operations practices. The pressure to innovate fast forces the adoption of approaches that used to be reserved for “cloud natives” or “web scale” companies. And so, decomposing apps with microservices, deploying to mixtures of traditional data center and cloud, and automating orchestration happens across enterprises. But it’s never one size fits all. Mixes of developer-lead innovation teams, virtualization teams, enterprise IT, and e-commerce sometimes work together and sometimes independently. After all, large enterprises are complex. [1] So how is the enterprise supposed ... Read More

Feed: Planet big data. Author: Curt Monash. August 22, 2017 I talked recently with the folks at Imanis Data. For starters: The point of Imanis is to make copies of your databases, for purposes such as backup/restore, test/analysis, or compliance-driven archiving. (That’s in declining order of current customer activity.) Another use is migration via restoring to a different cluster than the one that created the data in the first place. The data can come from NoSQL database managers, from Hadoop, or from Vertica. (Again, that’s in declining order.) As you might imagine, Imanis makes incremental backups; the only full backup ... Read More

Feed: All - O'Reilly Media. Author: Mary Treseler. Distribution Center (source: GRAPHICALBRAIN) ​This post is part of a series of Q&A interviews going behind the scenes with speakers from our October 2017 Velocity Conference in New York. Register for the O’Reilly Velocity Conference to join Joseph Breuer, Robert Reta, and other industry experts. Use code ORM20 to save 20% on your conference pass (Gold, Silver, and Bronze passes). I recently asked Joseph Breuer and Robert Reta, both Senior Software Engineers at Netflix, to discuss what they have learned through implementing a service at scale at Netflix. Joseph and Robert will ... Read More

Feed: All - O'Reilly Media. Author: Adam Michael Wood. Pyramid pattern. (source: Pixabay) In "Learning to Love Data Science," Mike Barlow looks at how organizations are using data science to turn information into wisdom and business value. Download a collection of free chapters from "Learning to Love Data Science." We are swimming in data. Or possibly drowning in it. Organizations and individuals are generating and storing data at a phenomenal and ever-increasing rate. The volume and speed of data collection has given rise to a host of new technologies and new roles focused on dealing with this data, managing it, ... Read More

Feed: Neo4j Graph Database. Author: Rachel Howard. By We analyzed the data and created a Gephi map of the 15,000 top users. One of the clusters we identified included journalists, the most prominent of whom was Washington Post reporter Because there was no budget, I had to use open source software and started with The original source code — the Python scripts and important routines for pulling this into Neo4j — is also still available on The key thing we learned in the research is that people are not disciplined about following the process of collecting data. Instead we typically ... Read More

Feed: Planet big data. Author: Julie Steele. August 17th, 2017 Editor’s note: Welcome to Throwback Thursdays! Every third Thursday of the month, we feature a classic post from the earlier days of our company, gently updated as appropriate. We still find them helpful, and we think you will, too! The original version of this post can be found here. Many enterprises are hoping to systematically drive competitive advantage and operational efficiency by gaining insight from data. For that reason, they may be contemplating — or already well into — a “data lake” effort. These are large, complex efforts, typically focussed ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Shreya Gupta. Introduction to Apache Spark Streaming? A data stream is an unbounded sequence of data arriving continuously. Streaming divides continuously flowing input data into discrete units for further processing. Stream processing is low latency processing and analyzing of streaming data. Spark Streaming was added to Apache spark in 2013, an extension of the core Spark API that provides scalable, high-throughput and fault-tolerant stream processing of live data streams. Data ingestion can be done from many sources like Kafka, Apache Flume, Amazon Kinesis or TCP sockets and processing can be done ... Read More

Feed: MariaDB Knowledge Base Article Feed. Author: . Nombre de la columna de soporte Es posible hacer referencia a la columna de nombres. Los nombres pueden usarse en cualquier lugar donde en MariaDB 5.3 se podría usar sólo cadenas: Crear una gota de columna dinámica: COLUMN_CREATE('int_col', 123 as int, 'double_col', 3.14 as double, 'string_col', 'text-data' as char); Establecer un valor de columna: COLUMN_ADD(dyncol_blob, 'intcol', 1234); Obtener un valor de columna: COLUMN_GET(dynstr, 'column1' as char(10)); Compruebe si existe una columna COLUMN_EXISTS(dyncol_blob, 'column_name'); Cambios en el comportamiento Columna salida de lista ahora incluye citar: select column_list(column_create(1, 22, 2, 23)); +------------------------------------------+ | column_list(column_create(1, ... Read More