Technology Innovations

Today, data-driven benefits abound. However, the ability to seize new business opportunities, create new products, and deal effectively with competitive issues requires strong data management and analytics capabilities. To help bring new resources and innovation to light, each year, Database Trends and Applications magazine presents the DBTA 100, a list of forward-thinking companies seeking to expand what's possible with data for their customers. Spanning the wide range of established to cutting edge, this year's DBTA 100 is a list of hardware, software, and service providers working to enable their customers' data-driven future. 

Competitive advantage in today’s world rests on a company’s ability to innovate and adapt to a rapidly changing environment. To do that, organizations must adopt real-time thinking in the way they approach the design, development and maintenance of their data infrastructure. Above all, that means dispensing with point-to-point integration and outdated batch processing methods that simply lack the necessary speed and agility to support competitive advantage in today’s world.

It's hard to know where to start when looking for the best MySQL GUI tools. Explore the top 10 packages now! 

Podman is a rising star in a new container landscape that suddenly has a lot more players. Learn what Podman is and how it compares to Docker for Kubernetes compatibility and more. 

The unique challenges resulting from the big data characteristics of volume, velocity and veracity require a new approach to data analysis. 

What are the top deep learning (DL) providers in the machine learning (ML) segment of the artificial intelligence (AI) market? 

From front-end JavaScript innovations to APIs as a service, today’s major trends in tools, technologies, and the cloud make it an exciting time to be a software developer.

Software development teams have resisted "big upfront designs" in favor of architectural designs emerging from self-organizing teams, which can lead to a mindset that software architecture is not really that important. Greater awareness of the implicit decisions they are making, and forcing these decisions to be made explicitly, can help development teams make better, more informed decisions. 

Updates announced at the company’s annual MongoDB World conference this week include new analytics capabilities, a data lake for its Atlas database as a service, and the ability to query encrypted data. 

Less than two years after its inception, Spring for GraphQL 1.0 has been released. The project integrates Spring and GraphQL Java and was developed in collaboration between both teams.

Cadence simplifies the complexity of distributed systems so that developers can focus on creating applications built for high durability, availability, and scalability. 

When Alex Watson co-founded the security company Harvest.ai back in 2014, using machine learning to identify sensitive data to protect it seemed like a good idea–so good, in fact, that AWS bought the company. Fast forward eight years, and Watson’s latest startup, Gretel.ai, is also using machine learning to stop security threats to data, but in an entirely different way.

The open source, massively parallel processing (MPP) analytical database will take on the likes of ClickHouse, MariaDB, Apache Druid, Apache Pinot, and hyperscaler services such as Google BigQuery, Amazon RedShift and Microsoft Synapse.

Snowflake last week promised analytics and transactions in the same system. For some it was déjà vu all over again.

It's easy for bias to permeate marketing campaigns when algorithms are used to target certain audiences; IBM is urging corporations to do something about it. 

As organizations have shifted from basic cloud environments to distributed environments, the cloud security strategies that sufficed five or 10 years ago are no longer enough. 

At some point when developing embedded applications, you're going to want to store unique values in non-volatile memory, values that can't be fixed at compilation time. Many microcontrollers have  a small amount of EEPROM memory for this very purpose, but it’s usually rather limited if it’s provided at all. Even if you do have a bit of space on an EEPROM at your disposal, actually formatting your values into the memory and dealing with the pesky problem of wear leveling (necessary for parameters that need to change often) can be a bit of a hassle.

In this article, Tejas Chopra discusses Netflix Drive, a generic cloud drive for storing and retrieving media assets - a collection of media files and folders in Netflix. Netflix Drive ties together disparate data (such as: AWS S3, Ceph Storage, Google Cloud Storage, and others) and metadata stores in a cogent form for creating, cataloging and serving these assets to applications and workflows. 

A mature framework for generating hybrid Java and JavaScript applications, JHipster supports the development tools you love and provides monitoring and other administrative  capabilities out of the box.

Companies can now get an Apache Airflow data orchestration environment up and running in less than an hour via Astro, a new managed service launched today.

Apache Beam is a stream processor, helping developers migrate work between different processes to offload work onto runners that leverage external resources. 

Kubecost introduces OpenCost, an open source project for monitoring Kubernetes spend, which provides real-time cost monitoring for teams running Kubernetes workloads.

As data management matures, unstructured data evolves from being a storage cost center to sitting at the epicenter of value creation. To make use of unstructured data for competitive gain, it’s important to develop a strategy for managing it to meet the dual needs of cost efficiency and monetization. Here is a 5-stage maturity model to follow for organizations looking to modernize unstructured data management practices.