Best Data Management Software for Red Hat OpenShift

IBM Instana sets the benchmark for incident prevention, offering comprehensive full-stack visibility with one-second precision and a notification time of just three seconds. In the current landscape of rapidly evolving and intricate cloud infrastructures, the financial repercussions of an hour of downtime can soar into the six-figure range or more. Conventional application performance monitoring (APM) tools often fall short, lacking the speed and depth required to effectively address and contextualize technical issues, and they usually necessitate extensive training for super users before they can be utilized effectively. In contrast, IBM Instana Observability transcends the limitations of standard APM tools by making observability accessible to a wider audience, enabling individuals from DevOps, SRE, platform engineering, ITOps, and development teams to obtain the necessary data and context without barriers. The Instana Dynamic APM functions through a specialized agent architecture, utilizing sensors—automated, lightweight programs specifically designed to monitor particular entities and ensure optimal performance. As a result, organizations can respond to incidents proactively and maintain a higher level of service continuity.

Appranix enables businesses to maintain resilience for their cloud applications, protecting against any potential downtime. The financial implications of an average ransomware attack can reach 4.54 million USD, with recovery efforts often taking around 26 days to complete. Notably, 14% of interruptions in cloud applications stem from misconfigurations, highlighting a significant area of risk. With its innovative strategies, Appranix offers unparalleled resilience for both distributed and dynamic cloud environments. The company's patented solutions—including continuous cloud infrastructure backups, cloud-native data backup and replication, combined with automated recovery-as-code capabilities—greatly minimize recovery time and the need for human intervention following cyber incidents or failures in cloud services or regions. Recognized as a Gartner Cool Vendor and ranked among the top three vendors by EMA, Appranix boasts a SaaS platform that is SOC II Type II certified and readily accessible across major marketplaces like AWS, Azure, GCP, VMware, and IBM/Redhat. As organizations face increasing threats in the digital landscape, Appranix stands out as a trusted partner for CTOs, CIOs, and cloud operations teams striving for the resilience crucial for success in today’s technology-driven environment. Embrace the future with Appranix and safeguard your cloud applications effectively.

Bacula Enterprise offers a single platform that provides cloud backup and recovery software for the Modern Data Center. Bacula Enterprise backup & recovery software is ideal for medium and large businesses. It offers unique innovation, modern architecture and business value benefits, as well as low cost of ownership. Bacula Enterprise corporate backup software solution uses unique technologies that increase the interoperability of Bacula Enterprise into many IT environments, such as managed service providers, software vendors, cloud providers, enterprise data centers, and cloud providers. Bacula Enterprise is used by thousands of organizations around the world in mission-critical environments such as NASA, Texas A&M University and Unicredit. Bacula offers more security features than other vendors and advanced hybrid Cloud connectivity to Amazon S3, Google, Oracle, and many others.

Keen is a fully managed event streaming platform. Our real-time data pipeline, built on Apache Kafka, makes it easy to collect large amounts of event data. Keen's powerful REST APIs and SDKs allow you to collect event data from any device connected to the internet. Our platform makes it possible to securely store your data, reducing operational and delivery risks with Keen. Apache Cassandra's storage infrastructure ensures data is completely secure by transferring it via HTTPS and TLS. The data is then stored with multilayer AES encryption. Access Keys allow you to present data in an arbitrary way without having to re-architect or re-architect the data model. Role-based Access Control allows for completely customizable permission levels, down to specific queries or data points.

Sedai intelligently finds resources, analyzes traffic patterns and learns metric performance. This allows you to manage your production environments continuously without any manual thresholds or human intervention. Sedai's Discovery engine uses an agentless approach to automatically identify everything in your production environments. It intelligently prioritizes your monitoring information. All your cloud accounts are on the same platform. All of your cloud resources can be viewed in one place. Connect your APM tools. Sedai will identify and select the most important metrics. Machine learning intelligently sets thresholds. Sedai is able to see all the changes in your environment. You can view updates and changes and control how the platform manages resources. Sedai's Decision engine makes use of ML to analyze and comprehend data at large scale to simplify the chaos.

Dataplane's goal is to make it faster and easier to create a data mesh. It has robust data pipelines and automated workflows that can be used by businesses and teams of any size. Dataplane is more user-friendly and places a greater emphasis on performance, security, resilience, and scaling.

Intel® Tiber™ AI Studio serves as an all-encompassing machine learning operating system designed to streamline and unify the development of artificial intelligence. This robust platform accommodates a diverse array of AI workloads and features a hybrid multi-cloud infrastructure that enhances the speed of ML pipeline creation, model training, and deployment processes. By incorporating native Kubernetes orchestration and a meta-scheduler, Tiber™ AI Studio delivers unparalleled flexibility for managing both on-premises and cloud resources. Furthermore, its scalable MLOps framework empowers data scientists to seamlessly experiment, collaborate, and automate their machine learning workflows, all while promoting efficient and cost-effective resource utilization. This innovative approach not only boosts productivity but also fosters a collaborative environment for teams working on AI projects.

SAS Visual Statistics allows for collaborative data exploration among multiple users, enabling them to interactively develop and refine predictive models. Data scientists and statisticians can leverage the most suitable analytical techniques to act on insights at a detailed level. Consequently, you will discover insights at remarkable speeds, uncovering new opportunities for revenue growth. The platform facilitates the construction and fine-tuning of models aimed at specific demographics or segments while simultaneously running various scenarios. This capability encourages users to pose numerous what-if questions to enhance outcomes. Additionally, results can be operationalized through automatically generated score code. Users are empowered to visually manipulate data by adding or adjusting variables, eliminating outliers, and more. Changes can be instantly assessed for their impact on the model's predictive accuracy, allowing for swift adjustments. Data science teams enjoy the ultimate flexibility by working in their preferred programming languages, maximizing their expertise. Ultimately, SAS Visual Statistics integrates all analytical resources, making it a comprehensive solution for data-driven decision-making. It fosters an environment where innovation can thrive, pushing the boundaries of what data analysis can achieve.

SAS® Viya® offers a robust and scalable analytics platform that is both efficient and easy to implement, allowing organizations to address a variety of business challenges. The insights generated automatically help in pinpointing the most frequently used variables across all models, highlighting key variables selected along with evaluation outcomes for each model. With the integration of natural language generation, project summaries are produced in straightforward language, which simplifies the interpretation of reports for users. Moreover, members of the analytics team can enhance the insights report with project notes, promoting better communication and teamwork. SAS further enables the integration of open source code within analyses, allowing users to utilize open source algorithms effortlessly in its platform. This flexibility encourages collaboration throughout your organization, as users are free to program in their preferred language. Additionally, you can leverage SAS Deep Learning with Python (DLPy), an open-source package available on GitHub, to expand your analytical capabilities even further. By using these tools, businesses can significantly enhance their data-driven decision-making processes.

Red Hat® Data Grid is a robust, in-memory distributed NoSQL database solution designed for high-performance applications. By enabling your applications to access, process, and analyze data at lightning-fast in-memory speeds, it ensures an exceptional user experience. With its elastic scalability and constant availability, users can quickly retrieve information through efficient, low-latency data processing that leverages RAM and parallel execution across distributed nodes. The system achieves linear scalability by partitioning and distributing data among cluster nodes, while also providing high availability through data replication. Fault tolerance is ensured via cross-datacenter geo-replication and clustering, making recovery from disasters seamless. Furthermore, the platform offers development flexibility and boosts productivity with its versatile and functionally rich NoSQL capabilities. Comprehensive data security features, including encryption and role-based access, are also included. Notably, the release of Data Grid 7.3.10 brings important security enhancements to address a known CVE. It is crucial for users to upgrade any existing Data Grid 7.3 installations to version 7.3.10 promptly to maintain security and performance standards. Regular updates ensure that the system remains resilient and up-to-date with the latest technological advancements.

A user-friendly, low-code visual platform allows for the creation and deployment of personalized chatbots that understand natural language. You can obtain text-based responses, retrieve data, generate reports and visualizations, and utilize analytics and AI through a conversational interface that feels intuitive. Within the SAS ecosystem, you can easily configure bots to enhance insight accessibility or link them to external services for broader outreach. Now, gaining insights from data is as straightforward as sending a simple message. Quickly identify significant relationships in your data with the help of smart suggestions and clearly marked related metrics. Leverage machine learning and natural language explanations to discover, visualize, and communicate compelling narratives and insights that are both accessible and easy to interpret. Investigate the reasons behind certain outcomes, explore all possibilities, and uncover hidden opportunities within your data. The system automatically highlights essential relationships, outliers, clusters, and more, unveiling crucial insights that can drive informed action and decision-making. This innovative approach empowers users to navigate complex data landscapes with confidence and clarity.