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RaimaDBRaimaDB is an embedded time series database designed specifically for Edge and IoT devices, capable of operating entirely in-memory. This powerful and lightweight relational database management system (RDBMS) is not only secure but has also been validated by over 20,000 developers globally, with deployments exceeding 25 million instances. It excels in high-performance environments and is tailored for critical applications across various sectors, particularly in edge computing and IoT. Its efficient architecture makes it particularly suitable for systems with limited resources, offering both in-memory and persistent storage capabilities. RaimaDB supports versatile data modeling, accommodating traditional relational approaches alongside direct relationships via network model sets. The database guarantees data integrity with ACID-compliant transactions and employs a variety of advanced indexing techniques, including B+Tree, Hash Table, R-Tree, and AVL-Tree, to enhance data accessibility and reliability. Furthermore, it is designed to handle real-time processing demands, featuring multi-version concurrency control (MVCC) and snapshot isolation, which collectively position it as a dependable choice for applications where both speed and stability are essential. This combination of features makes RaimaDB an invaluable asset for developers looking to optimize performance in their applications.
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Google Compute EngineGoogle's Compute Engine, which falls under the category of infrastructure as a service (IaaS), enables businesses to create and manage virtual machines in the cloud. This platform facilitates cloud transformation by offering computing infrastructure in both standard sizes and custom machine configurations. General-purpose machines, like the E2, N1, N2, and N2D, strike a balance between cost and performance, making them suitable for a variety of applications. For workloads that demand high processing power, compute-optimized machines (C2) deliver superior performance with advanced virtual CPUs. Memory-optimized systems (M2) are tailored for applications requiring extensive memory, making them perfect for in-memory database solutions. Additionally, accelerator-optimized machines (A2), which utilize A100 GPUs, cater to applications that have high computational demands. Users can integrate Compute Engine with other Google Cloud Services, including AI and machine learning or data analytics tools, to enhance their capabilities. To maintain sufficient application capacity during scaling, reservations are available, providing users with peace of mind. Furthermore, financial savings can be achieved through sustained-use discounts, and even greater savings can be realized with committed-use discounts, making it an attractive option for organizations looking to optimize their cloud spending. Overall, Compute Engine is designed not only to meet current needs but also to adapt and grow with future demands.
What is xiRAID?
xiRAID is an advanced RAID solution designed specifically for the requirements of modern storage systems, particularly those that utilize NVMe and NVMe-over-Fabrics (NVMe-oF) technologies. By moving away from traditional hardware RAID controllers, it embraces a software-driven architecture that not only boosts performance but also lowers overall ownership costs and enhances operational adaptability. This solution supports both locally connected drives and networked NVMe devices, serving as a unified block device that applications can access without necessitating any modifications. Aimed at achieving performance metrics that rival those of hardware, xiRAID utilizes advanced techniques like I/O parallelization and a lockless datapath, reaching remarkable throughput speeds of up to 150 GB/s, managing up to 30 million IOPS, and keeping latency below 0.5 ms, all while consuming minimal CPU and memory resources. With support for various RAID configurations, including levels 0, 1, 5, 6, 10, 50, 60, and 70, it integrates effortlessly with existing file systems through its compatibility with POSIX APIs. Overall, xiRAID is not just a robust solution; it is also a highly adaptable one, ready to cater to the dynamic demands of data-heavy applications. Its ability to evolve in response to changing technology trends ensures that it remains a leading choice for enterprises looking to optimize their storage infrastructure.
What is Datafy?
Datafy empowers organizations to effectively control their cloud storage costs by automating the optimization of Amazon EBS volumes through persistent monitoring and right-sizing, guaranteeing that expenditures accurately reflect actual usage. The platform provides valuable insights into volume utilization, enables policy-driven resizing with zero downtime or manual intervention, and promotes ongoing savings by dynamically adjusting capacity and identifying underutilized or dormant volumes. It operates through a systematic three-step approach: initially, it examines the storage landscape for inefficiencies; subsequently, it enhances performance by automatically resizing volumes in accordance with usage patterns; and ultimately, it secures continuous savings by maintaining an efficient storage footprint. By effortlessly integrating with existing cloud infrastructures, Datafy functions quietly in the background to streamline storage management, reduce waste, and maintain operational uptime. Users have reported substantial cost reductions while utilizing Datafy, and the setup process is remarkably smooth and efficient. This user-friendly experience allows organizations to concentrate on their primary functions while reaping the benefits of optimized storage solutions, fostering a more productive operational environment. As a result, companies can not only save money but also enhance their overall efficiency in managing cloud resources.
Integrations Supported
Amazon Elastic Block Store (EBS)
Amazon Web Services (AWS)
Integrations Supported
Amazon Elastic Block Store (EBS)
Amazon Web Services (AWS)
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Xinnor
Date Founded
2022
Company Location
India
Company Website
xinnor.io/what-is-xiraid/
Company Facts
Organization Name
Datafy
Date Founded
2023
Company Location
Israel
Company Website
datafy.io