Dragonfly
Dragonfly serves as a seamless substitute for Redis, offering enhanced performance while reducing costs. It is specifically engineered to harness the capabilities of contemporary cloud infrastructure, catering to the data requirements of today’s applications, thereby liberating developers from the constraints posed by conventional in-memory data solutions. Legacy software cannot fully exploit the advantages of modern cloud technology. With its optimization for cloud environments, Dragonfly achieves an impressive 25 times more throughput and reduces snapshotting latency by 12 times compared to older in-memory data solutions like Redis, making it easier to provide the immediate responses that users demand. The traditional single-threaded architecture of Redis leads to high expenses when scaling workloads. In contrast, Dragonfly is significantly more efficient in both computation and memory usage, potentially reducing infrastructure expenses by up to 80%. Initially, Dragonfly scales vertically, only transitioning to clustering when absolutely necessary at a very high scale, which simplifies the operational framework and enhances system reliability. Consequently, developers can focus more on innovation rather than infrastructure management.
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ManageEngine ADAudit Plus
ADAudit Plus enhances the security and compliance of your Windows Server environment by delivering comprehensive insights into all operational activities. It offers a detailed overview of modifications made to Active Directory (AD) resources, encompassing AD objects and their respective attributes, group policies, and more. By conducting thorough AD audits, organizations can identify and mitigate insider threats, misuse of privileges, and other signs of potential security breaches, thereby bolstering their overall security framework. The tool enables users to monitor intricate details within AD, including entities such as users, computers, groups, organizational units (OUs), group policy objects (GPOs), schemas, and sites, along with their associated attributes. Furthermore, it tracks user management activities like the creation, deletion, password resets, and alterations in permissions, providing insights into the actions taken, the responsible individuals, the timing, and the originating locations. Additionally, it allows organizations to monitor the addition or removal of users from security and distribution groups, ensuring that access privileges are kept to the necessary minimum, which is critical for maintaining a secure environment. This level of oversight is vital for proactive security management and compliance adherence.
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K2View
K2View believes that every enterprise should be able to leverage its data to become as disruptive and agile as possible.
We enable this through our Data Product Platform, which creates and manages a trusted dataset for every business entity – on demand, in real time. The dataset is always in sync with its sources, adapts to changes on the fly, and is instantly accessible to any authorized data consumer.
We fuel operational use cases, including customer 360, data masking, test data management, data migration, and legacy application modernization – to deliver business outcomes at half the time and cost of other alternatives.
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AWS Glue
AWS Glue is a fully managed data integration solution that simplifies the process of discovering, preparing, and merging data for purposes such as analytics, machine learning, and application development. By offering all the necessary tools for data integration, AWS Glue enables users to begin analyzing their data and leveraging it for insights within minutes rather than taking months. The concept of data integration encompasses various activities like identifying and extracting data from multiple sources, enhancing, cleaning, normalizing, and consolidating that data, as well as organizing and loading it into databases, data warehouses, and data lakes. Different users, each utilizing various tools, often manage these tasks. Operating within a serverless environment, AWS Glue eliminates the need for infrastructure management, automatically provisioning, configuring, and scaling the resources essential for executing data integration jobs. This efficiency allows organizations to focus more on data-driven decision-making without the overhead of manual resource management.
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