by Angela Guess A new press release reports, ?Actian, the hybrid data management, analytics and integration company, today announced new multi-platform editions of the industry leading Actian Zen Embedded database solution family designed to address the demanding scale-down and scale-out requirements of data-centric IoT solutions. This innovative offering provides the industry with the first enterprise-ready [?]
SQL developers on every platform are struggling, seemingly stuck in a DO WHILE loop that makes them repeat the same mistakes again and again. That?s because the database field is still relatively immature. Sure, vendors are making some strides, but they continue to grapple with the bigger issues. Concurrency, resource management, space management, and speed still plague SQL developers whether they?re coding on SQL Server, Oracle, DB2, Sybase, MySQL, or any other relational platform.
In the last few years, AI has made breathtaking strides driven by developments in machine learning, such as deep learning. Deep learning is part of the broader field of machine learning that is concerned with giving computers the ability to learn without being programmed. Deep learning has had some incredible successes.
Click to learn more about author Paul Stanton. There is a disconnect between the goals of DevOps, and the realities of working with relational data. Relational databases are core to many enterprise applications, and the Gartner Group projects that 80% of new projects will rely on relational data through 2020 (available courtesy of Microsoft here). [?]
You might have gone into an alcohol-induced hibernation over the holidays, but cloud databases did not. More specifically, the cumbersomely named Microsoft Azure Cosmos DB did not, rocketing past AWS Redshift, as Begin founder Brian Leroux first noticed. While everything was ?as you were? for AWS database leader DynamoDB in 2017, according to DB Engines? comprehensive ranking, Cosmos DB jumped 27 places, from 58 to 31.
Click to learn more about author Dipti Borkar. Organizations have spent the past few years educating themselves on various Artificial Intelligence frameworks and tools. But for AI to become mainstream, it will need move beyond small-scale and often ad hoc experiments being run by Data Scientists, to becoming an automated pipeline with the inference and [?]
by Angela Guess A recent press release states, ?Rocket Software, a global technology provider specializing in app modernization and systems optimization, announced today that Rocket® UniData, part of the Rocket MultiValue Application Platform, is a Database Trends and Applications 2018 Trend-Setting Product. The inclusion marks the third year in a row that Database Trends and [?]
I?m one of those people who takes time at the new year to define personal objectives for the forthcoming year, some of which I actually achieve. Enterprise IT should be doing the same thing for cloud computing.
Click to learn more about author Thomas LaRock Clouds consist of tiny droplets of water or ice crystals?hydrogen and oxygen. The Earth is made up mainly of iron, oxygen, silicon and magnesium. You wouldn?t expect these different combinations of elements to act the same, nor should you assume that your Cloud servers will function exactly like [?]
There are a lot of disputes about the prospects of this technology; someone predicts a great future for it. Other analysts are confident that the excitement around this industry will soon fall. But one thing that we know for sure, if you need any help with writing a good essay,... Read more »
Click to learn more about author Stuart Tarmy. Data Flow allows a company to understand the relationships between data elements across the enterprise and between individual lines of business. Companies in a wide range of industries, including financial services, health care, aviation and energy services, are increasingly focused on Data Flow to better leverage their Data [?]
Trends in Data Analytics ? From Database to Analyst from DATAVERSITY To view the On Demand recording from this presentation, click HERE>> About the Webinar How are the tools and skills needed for data analytics changing? Why has there been an expansion of the databases used in data analytics to the new class of NoSQL [?]
To view just the slides from this presentation, click HERE>> About the Webinar How are the tools and skills needed for data analytics changing? Why has there been an expansion of the databases used in data analytics to the new class of NoSQL to handle the volumes, variety, and velocity of big data. What are [?]
One of the most fundamental choices to make when developing an application is whether to use a SQL or NoSQL database to store the data. Conventional SQL (i.e. relational) databases are the product of decades of technology evolution, good practice, and real-world stress testing. They are designed for reliable transactions and ad hoc queries, the staples of line of business applications. But they also come burdened with restrictions?such as rigid schema?that make them less suitable for other kinds of apps.
PostgreSQL (aka Postgres) is old as dirt, yet over the past five years it has panned out as pure gold. MongoDB got the billion-dollar IPO and AWS launched the mind-bendingly cool Aurora Serverless, but it?s PostgreSQL that keeps having its moment?again and again and again.
2017 has been a pivotal year for the database technologies market, with several massive paradigm shifts that shows no signs of stopping anytime soon. Companies are pivoting away from the traditional monolithic database architectures which, for decades, powered generations after generations of applications in exchange for a more optimized, agile, self-managed cloud-focused data platform strategy.
Click to learn more about author Paul Stanton. Cloud Computing and DevOps are dominant themes in computing today. AWS, Azure, Google, and others compete to provide greater agility, while reducing enterprise cost of building, running, and protecting information services. Progress is being made in DevOps strategies, with new leadership and organizational culture, combined with tools [?]
by Angela Guess A new press release states, ?Redis Labs, the home of Redis and provider of Redis Enterprise, today announced that Redis Enterprise is now available with Active-Active geographic distribution. The use of cutting-edge CRDT (Conflict Free Replicated Datatypes) technology allows Redis databases to be deployed globally yet provide local latencies for writes and [?]
by Angela Guess According to a recent press release, ?MariaDB® Corporation, the company behind the fastest growing open source database, today announced new product enhancements to MariaDB AX, delivering a modern approach to data warehousing that enables customers to easily perform fast and scalable analytics with better price performance over proprietary solutions. MariaDB AX expands [?]
Click to learn more about author Thomas Frisendal. ?Nudge nudge, wink wink, say no more, say no more?. Says British Eric Idle in the third Monty Python?s Flying Circus episode, ?How to Recognise Different Types of Trees From Quite a Long Way Away? from 1969. Indeed, it should not be necessary to say more, once [?]
by Angela Guess A recent press release states, ?Companies and developers wanting to integrate the decentralization, immutability, and consensus benefits of blockchain technology into their existing data infrastructure and business applications finally have an enterprise-grade product with which to do so. FlureeDB ? a scalable, blockchain cloud database ? launched November 9th, 2017 for public [?]
Click to learn more about author Richard Macaskill. We all know GDPR is on the way and, to date, most of the articles have been industry-focused, talking about the affect it will have on companies and organizations that gather, hold and process data. I recently wrote about why DBAs should care about it, and advised that [?]
Big Data refers to extremely large data sets of varying types of data ? structured, unstructured, and semi-structured ? that can be collected, stored, and later analyzed to provide insights for organizations. Big Data?s promise depends on how the data is managed. In the past data was organized in relational models, sometimes within Data Warehouses, [?]