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  • What is simplyblock?
    Simplyblock is a cross-cloud software-defined storage platform that powers next-gen workloads such as AI, ML, HPC or modern databases, while reducing cost and complexity for cloud service providers. Simplyblock's technology delivers ultra-high performance at low total cost of ownership (TCO), offering compatibility with any cloud, platform or hardware and easy, fully containerised, deployment. Up to 100x improved cost-to-performance over currently prevailing software-defined storage technologies like Ceph.
  • What is the innovation in simplyblock's solution?
    Our SDS solution comes with multiple levels of innovation: It is specifically designed for the nvme standard and ssds, meeting access latency, storage efficiency and security benchmarks of best-in-class SAN systems, based on commodity hardware, which is at least by a factor of 10 cheaper compared to those systems It works of standard GbE and TCP/IP and does not require any special storage networking technology in the data center It is extremely scalable - adding hardware and storage capacity to a single system will linearly increase available throughput and keep access latency stable despite of increasing load - up to multi-rack deployments with thousands of storage drives - there is no conventional SAN system available that scales similarly It runs both on cloud native infrastructure and on standard server hardware in conventional data centers and is architected to solve critical data storage challenges in hybrid (combined cloud and non-cloud) environments and massively simplify the overall data storage architecture in these environments
  • What are key technical features of simplyblock's software?
    Software-defined, high-performance, highly scalable shared block storage system for cloud, hybrid cloud and non-cloud deployments Cost / TB ca. 10 times lower than competitive products and high-performance cloud storage Can deliver up to 100,000 IOPS per single TB with linear performance scalability to thousands of TB in a cluster Standard features Ultra-Fast asynchronous compression and inline decompression Cluster-wide deduplication can save storage capacity by a factor of 10 and more Cluster-wide logical volumes with thin provisioning, snapshots, clones Storage capacity and load remains perfectly balanced across the whole cluster over time - even if new capacity is added or capacity is removed Very easy to add new capacity (storage drives and nodes) to the cluster and replace existing hardware with the same or other models and even vendors - required data migrations and rebuilds are fully automated and transparent Runs in both native cloud environments (on dedicated servers) and non-cloud data centers.
  • Why is simplyblock's solution secure?
    Simplyblock is keeping your data safe from disaster or satisfying a need for redundant storage is mission-critical. Block storage is separate from your local server, providing a safe and secure method of storing your data. Additionally, simplyblock offers data encryption features which means that you don't need to build, maintain, and secure your own key management infrastructure.
  • What is software-defined data storage?
    Software-defined storage (SDS) is a type of storage architecture that separates the storage software from the underlying hardware, allowing the storage capabilities of the system to be managed and controlled through software. This architecture is designed to provide organizations with more flexibility and control over their storage infrastructure, as well as to be more cost-effective and easier to manage than traditional storage systems. In a traditional storage system, the storage hardware and software are tightly coupled, which means that the hardware and software are designed to work together and cannot be easily separated. In contrast, in a software-defined storage system, the storage software is decoupled from the hardware, which allows the software to be run on a wide range of hardware platforms. This allows organizations to choose the hardware that best meets their needs and to easily change hardware as their needs evolve. Software-defined storage systems can be used to store and manage a wide range of data types, including structured and unstructured data, and they can support a variety of storage protocols, such as Fibre Channel, iSCSI, and NFS. SDS systems can be deployed on-premises or in the cloud, and they can be used to support a wide range of applications, including data analytics, big data, and cloud storage.
  • Who needs software-defined block data storage?
    Data block storage is a type of storage that is used to store large amounts of data, typically in the form of blocks. Data block storage is often used by organizations that have a large amount of data that needs to be stored, accessed, and managed in a efficient and cost-effective way. Some examples of organizations that may need data block storage include: Enterprise companies: Enterprise companies often have large amounts of data that need to be stored and managed, such as customer data, financial data, and operational data. Data block storage can provide a scalable and reliable way to store and manage this data. Cloud service providers: Cloud service providers offer storage and computing resources to their customers, and data block storage can be an important part of their infrastructure. By using data block storage, cloud service providers can offer their customers scalable and reliable storage for their data. Media and entertainment companies: Media and entertainment companies often need to store and manage large amounts of data, such as video and audio files. Data block storage can provide a cost-effective and scalable solution for storing and managing this type of data. Research institutions: Research institutions often need to store and manage large amounts of data, such as scientific data, research papers, and images. Data block storage can provide a reliable and scalable solution for storing and managing this data. Government: Governments generate and manage a large amount of data, including data related to citizens, public services, and operations. Data block storage can be used to store and manage this data in a secure and efficient way.
  • What is the advantage of software-defined storage over SAN?
    Software-defined storage (SDS) is a type of storage architecture in which the storage software is decoupled from the hardware and runs on standard servers. This allows the storage capabilities of the system to be managed and controlled through software, rather than being tied to specific hardware. One of the main advantages of SDS over storage area networks (SANs) is that it allows for more flexibility and scalability. Because the storage software is decoupled from the hardware, it can be easily moved and run on different servers as needed. This makes it easier to add or remove storage capacity, and to allocate resources as needed. SDS systems also tend to be more cost-effective than SANs, because they use standard servers rather than specialized storage hardware. This can make SDS an attractive option for organizations that need to store large amounts of data but want to do so in a cost-effective way. Another advantage of SDS is that it can be more easily integrated with other software-defined infrastructure, such as software-defined networking (SDN). This can make it easier for organizations to manage and control their entire IT infrastructure through software.
  • What are the key problems with SAN storage systems?
    Storage area networks (SANs) are a type of network that provides access to shared storage resources. There are a few key problems that can arise with SAN storage systems: Complexity: SAN systems can be complex to set up and maintain, especially for larger organizations. They require specialized hardware and software, and they often involve multiple components that need to be configured and managed separately. Scalability: It can be challenging to scale a SAN system as the storage needs of an organization grow. Adding additional storage capacity often requires the purchase of additional hardware, which can be expensive and time-consuming. Performance: SAN systems can suffer from performance issues, especially when there is a high volume of data being transferred. This can lead to slowdowns and bottlenecks, which can impact the overall performance of the system. Downtime: SAN systems are vulnerable to downtime, which can occur for a variety of reasons, including hardware failures, network outages, and software glitches. Downtime can be costly for organizations, as it can disrupt business operations and lead to lost productivity. Cost: SAN systems can be expensive to set up and maintain, especially for larger organizations. The cost of hardware, software, and ongoing maintenance can add up quickly, making it a challenging investment for some organizations.
  • What are the problems related to growing data volumes?
    Growing data volumes can present a number of challenges for organizations, including: Storage capacity: As data volumes grow, it can be difficult for organizations to find sufficient storage capacity to store all of their data. This can lead to the need to purchase additional storage hardware or to move data to the cloud, which can be costly and time-consuming. Data management: Managing and organizing large amounts of data can be challenging, especially if the data is not properly structured or if it is spread across multiple systems. This can make it difficult to access and use the data effectively. Data security: Ensuring the security of large volumes of data can be a significant challenge, as it requires robust security measures and protocols to protect against data breaches and other threats. Data analysis: Analyzing large volumes of data can be time-consuming and resource-intensive, and it can be difficult to extract meaningful insights from the data. Cost: Storing and managing large volumes of data can be expensive, as it requires a significant investment in hardware, software, and ongoing maintenance. Overall, growing data volumes can present significant challenges for organizations, and it is important for organizations to have a well-thought-out plan for addressing these challenges in order to effectively manage their data.
  • What are the limitations of typical cloud storage?
    Cloud storage is a type of storage that involves storing data on remote servers that are accessed over the internet, rather than on local servers or devices. While cloud storage has many benefits, there are also a few limitations to be aware of: Internet connectivity: Cloud storage relies on an internet connection to access and transfer data. If the internet connection is slow or unreliable, it can impact the performance of the storage system. Security: While cloud storage providers take steps to secure data, there is always a risk of data breaches or cyber attacks. It is important for organizations to carefully evaluate the security measures of a cloud storage provider before entrusting them with sensitive data. Cost: While cloud storage can be cost-effective compared to traditional storage systems, it can become expensive for organizations with very large amounts of data or for organizations that need to store data with very high durability requirements. Vendor lock-in: Organizations that use cloud storage may become dependent on a particular vendor and may face challenges if they want to switch to a different provider. It is important for organizations to carefully consider the long-term implications of using a particular cloud storage provider. Compliance: Some industries have strict regulations around the storage and handling of data, and it may be difficult for organizations to meet these requirements using cloud storage. Overall, while cloud storage has many benefits, it is important for organizations to carefully evaluate the limitations and consider how they may impact their specific needs and requirements.
  • What are the limitations of PostgreSQL service on AWS RDS?
    Amazon Web Services (AWS) offers a managed PostgreSQL service called Amazon RDS for PostgreSQL. This service makes it easy for organizations to set up, operate, and scale PostgreSQL databases in the cloud. There are a few limitations to be aware of when using Amazon RDS for PostgreSQL: Limited control over the underlying infrastructure: As a managed service, Amazon RDS for PostgreSQL does not provide direct access to the underlying infrastructure. This means that you do not have control over the operating system or the hardware that your database is running on. Limited customization: Amazon RDS for PostgreSQL does not allow for much customization of the database engine. This means that you cannot install additional extensions or modify the configuration of the database engine in the same way that you could if you were running PostgreSQL on your own infrastructure. No support for certain features: Amazon RDS for PostgreSQL does not support certain features that are available in the open-source version of PostgreSQL, such as replication slots and logical decoding. Performance limitations: While Amazon RDS for PostgreSQL can scale to handle large workloads, there may be some performance limitations depending on the size of the instance you are using. Cost: Amazon RDS for PostgreSQL is a pay-as-you-go service, which means that you will be charged for the resources you use. Depending on your usage patterns, this can potentially be more expensive than running your own PostgreSQL databases on your own infrastructure.
  • What are the challenges with data disaster recovery solutions for SMEs?
    Small and medium-sized enterprises (SMEs) face a number of challenges when it comes to data disaster recovery, including: Limited resources: SMEs often have limited resources, including budget and personnel, which can make it challenging to implement and maintain a robust data disaster recovery plan. Complexity: Implementing a data disaster recovery plan can be complex, especially for SMEs that have limited IT expertise and experience. Cost: Data disaster recovery solutions can be expensive, especially for SMEs that have large amounts of data to protect. Lack of awareness: Some SMEs may not be aware of the importance of data disaster recovery or may not understand the options available to them. Limited data protection: Some SMEs may not have the necessary data protection measures in place, such as backup and recovery systems, which can make it more difficult to recover from a disaster. To address these challenges, SMEs can use simplyblock's data disaster recovery solution that seamlessly integrates with their IT environment and replicates data between the data center of choice and the cloud (AWS).
  • What are the challenges of setting up hybrid cloud environment?
    Hybrid cloud is a type of cloud computing architecture that combines on-premises infrastructure with one or more public cloud services. Setting up a hybrid cloud can be challenging, as it involves integrating and managing multiple different types of infrastructure and technologies. Some specific challenges of setting up a hybrid cloud include: Integration: Integrating on-premises infrastructure with one or more public cloud services can be complex, as it requires coordinating and managing different systems, protocols, and processes. Security: Ensuring the security of data and systems in a hybrid cloud environment can be challenging, as it requires implementing robust security measures and protocols to protect against threats and vulnerabilities. Governance: Managing and governing a hybrid cloud environment can be complex, as it involves establishing policies and procedures for data management, access control, and compliance. Cost: Implementing and maintaining a hybrid cloud environment can be expensive, especially for organizations that have large amounts of data or complex hybrid cloud architectures. Skills and expertise: Setting up and managing a hybrid cloud environment requires a deep understanding of multiple different technologies and architectures, which can be a challenge for organizations that do not have the necessary skills and expertise in-house. Simplyblock helps customers to set up hybrid cloud environments and connect their data between cloud (AWS) and data center of choice.

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