IBM Cloud Object Storage Integrations

QuantaStor, a unified Software Defined Storage platform, is designed to scale up and down to simplify storage management and reduce overall storage costs. QuantaStor storage grids can be configured to support complex workflows that span datacenters and sites. QuantaStor's storage technology includes a built-in Federated Management System that allows QuantaStor servers and clients to be combined to make management and automation easier via CLI and RESTAPIs. QuantaStor's layered architecture gives solution engineers unprecedented flexibility and allows them to design applications that maximize workload performance and fault tolerance for a wide variety of storage workloads. QuantaStor provides end-to-end security coverage that allows multi-layer data protection for cloud and enterprise storage deployments.

Sematext Cloud provides all-in-one observability solutions for modern software-based businesses. It provides key insights into both front-end and back-end performance. Sematext includes infrastructure, synthetic monitoring, transaction tracking, log management, and real user & synthetic monitoring. Sematext provides full-stack visibility for businesses by quickly and easily exposing key performance issues through a single Cloud solution or On-Premise.

RcloneView, a GUI client for Rclone designed to simplify cloud data management on Windows, Mac and Linux, is an easy-to-use GUI client. RcloneView's intuitive design allows users to manage, sync, and backup files across a variety of cloud storage services including Google Drive (including Amazon S3), Dropbox, WebDAV and FTP. The softwarsimplifies the complexity associated with command-line operations and makes it accessible to both casual users as well as IT professionals. Key Features • File browsing: Browse, copy, move and delete files across all cloud platforms. • Job Automation: Schedule and save sync tasks to streamline workflows. • 1:N Synchronization: Sync multiple destinations from a single source in one step. • Cloud Mounting - Mount cloud storage as local disks for seamless file management. • Multi-Window management: Manage multiple Rclone connections at the same time. • Transfer Tracking: Monitor the progress of file transfers and access detailed logs.

3 Drive connects with any standard S3 data store. This allows you to work with cloud files virtually as if they were on your local filesystem. The S3 API allows you to access, update, edit and save files in any storage service that supports the S3 protocol, including: Amazon S3, Google Cloud Storage (including Blob Storage), Microsoft Azure Blob Storage (including IBM Cloud Object Storage), Backblaze B2, Wasabi and DigitalOcean. S3 Drive adds an additional layer of local cache on top the S3 API. This allows files to be saved locally and uploaded automatically, so you do not have to upload or download files every time. Powerful Capabilities - Store multiple connection profiles for a quick, convenient connection. S3 Drive features FIPS mode. - Run S3 Drive as a Windows service or desktop application. Use S3 Drive from the command-line or as a desktop application. S3 Drive supports Windows Arm64. - Available on Windows, Linux and macOS. S3 Drive is trusted worldwide by the largest technology companies.

Experience serverless and interactive data querying with IBM Cloud Object Storage, enabling you to analyze your data directly at its source without the need for ETL processes, databases, or infrastructure management. IBM Cloud SQL Query leverages Apache Spark, a high-performance, open-source data processing engine designed for quick and flexible analysis, allowing SQL queries without requiring ETL or schema definitions. You can easily perform data analysis on your IBM Cloud Object Storage via our intuitive query editor and REST API. With a pay-per-query pricing model, you only incur costs for the data that is scanned, providing a cost-effective solution that allows for unlimited queries. To enhance both savings and performance, consider compressing or partitioning your data. Furthermore, IBM Cloud SQL Query ensures high availability by executing queries across compute resources located in various facilities. Supporting multiple data formats, including CSV, JSON, and Parquet, it also accommodates standard ANSI SQL for your querying needs, making it a versatile tool for data analysis. This capability empowers organizations to make data-driven decisions more efficiently than ever before.

IBM Analytics Engine offers a unique architecture for Hadoop clusters by separating the compute and storage components. Rather than relying on a fixed cluster with nodes that serve both purposes, this engine enables users to utilize an object storage layer, such as IBM Cloud Object Storage, and to dynamically create computing clusters as needed. This decoupling enhances the flexibility, scalability, and ease of maintenance of big data analytics platforms. Built on a stack that complies with ODPi and equipped with cutting-edge data science tools, it integrates seamlessly with the larger Apache Hadoop and Apache Spark ecosystems. Users can define clusters tailored to their specific application needs, selecting the suitable software package, version, and cluster size. They have the option to utilize the clusters for as long as necessary and terminate them immediately after job completion. Additionally, users can configure these clusters with third-party analytics libraries and packages, and leverage IBM Cloud services, including machine learning, to deploy their workloads effectively. This approach allows for a more responsive and efficient handling of data processing tasks.

Unify all your data sources, encompassing both relational and NoSQL databases, SaaS applications, and APIs, allowing you to query them as if they were a single data entity instantly. Process data at its source without delay, enabling you to query, cache, and merge information from various origins seamlessly. Utilize webhooks to bring in real-time streaming data from platforms like Kafka and Segment into the Peaka BI Table, moving away from the traditional nightly batch ingestion in favor of immediate data accessibility. Approach every data source as though it were a relational database, transforming any API into a table that can be integrated and joined with your other datasets. Employ familiar SQL syntax to execute queries in NoSQL environments, allowing you to access data from both SQL and NoSQL databases using the same skill set. Consolidate your data to query and refine it into new sets, which you can then expose through APIs to support other applications and systems. Streamline your data stack setup without becoming overwhelmed by scripts and logs, and remove the complexities associated with building, managing, and maintaining ETL pipelines. This approach not only enhances efficiency but also empowers teams to focus on deriving insights rather than being bogged down by technical hurdles.

Ensure that your data is always accessible, secure, and cost-effective by utilizing Tiger Bridge. This innovative solution seamlessly links your locally stored data to various storage options, including cloud, tape, and disk, while maintaining its original format for easy access. Tiger Bridge operates purely as software, eliminating the need for extra hardware or virtual appliances, and its installation and configuration are completed in mere minutes, making it user-friendly. Setting up policies is a simple process, and the integration occurs at either the file system level or through network sharing. As your team continues their work, the policies run quietly in the background, automatically replicating data to your preferred storage solution. Maximize your hardware investment by extending storage capabilities to the cloud with a flexible pay-as-you-go approach. Designed to accommodate data sets of any scale, Tiger Bridge optimizes storage configurations for even the most intensive workflows, catering to a range of industries, from post-production studios and civil engineering firms to expansive medical institutions. With Tiger Bridge, you can streamline your data management process while ensuring scalability and efficiency for future demands.

Deploying OpenShift applications with watsonx can be achieved easily through two adaptable options tailored for hybrid cloud requirements. The Fusion HCI System offers a comprehensive, ready-to-use platform designed for the seamless operation of your on-premises Red Hat OpenShift applications. With Fusion software, you can utilize any environment where Red Hat OpenShift is supported—including public cloud, on-premises systems, bare metal, and virtual machines. This solution integrates hardware, Red Hat OpenShift, and data services, effectively removing compatibility challenges and minimizing setup time, which allows you to launch your containerized applications rapidly, thus fostering quicker innovation and a shorter time-to-market. Additionally, it streamlines the infrastructure and data services necessary for OpenShift applications, enabling platform engineers to manage OpenShift from a central point, enhance operational efficiency, optimize resource use, and lower both operational complexities and costs, making it a robust choice for modern application deployment.

If you're looking to establish a governed delta lake, create a data warehouse, or transition from a conventional database to a contemporary cloud data solution, Lyftrondata has you covered. You can effortlessly create and oversee all your data workloads within a single platform, automating the construction of your pipeline and warehouse. Instantly analyze your data using ANSI SQL and business intelligence or machine learning tools, and easily share your findings without the need for custom coding. This functionality enhances the efficiency of your data teams and accelerates the realization of value. You can define, categorize, and locate all data sets in one centralized location, enabling seamless sharing with peers without the complexity of coding, thus fostering insightful data-driven decisions. This capability is particularly advantageous for organizations wishing to store their data once, share it with various experts, and leverage it repeatedly for both current and future needs. In addition, you can define datasets, execute SQL transformations, or migrate your existing SQL data processing workflows to any cloud data warehouse of your choice, ensuring flexibility and scalability in your data management strategy.

Utilizing log services is essential, yet your teams desire insights at the cluster level. Enhance efficiency and obtain more profound insights with IBM® Log Analysis service, which offers seamless integration with numerous cloud-native runtimes and environments. Experience features such as log collection, log tailing, and rapid log searches. Benefit from natural language queries and a search retention period of up to 30 days. You can set up cluster-level logging for Kubernetes clusters, providing access to logs for various types, including worker, pod, application, and network logs. This data can be monitored from diverse sources, allowing for centralized management of Ubuntu logs on IBM Cloud®. DevOps teams have the capability to archive logs from an IBM Log Analysis instance directly into a bucket within an IBM Cloud Object Storage instance. By aggregating all log data in one central location, you can anticipate compatibility with services like Pager Duty, Slack, webhooks, and many others. The service supports over 30 integrations and ingestion sources, while also offering features like natural language queries and a pay-per-GB pricing model. This comprehensive approach not only simplifies log management but also empowers teams to gain actionable insights quickly.

Evaluate essential performance metrics for your storage, SAN, and LAN equipment to enhance your vital IT infrastructure. This approach offers a comprehensive mapping visualization across cloud services, containerization, server virtualization, and databases. Its leading performance-monitoring tool features a unique web-based interface that allows for graphical analysis of performance utilization within a virtualized setting. Users can easily access the utilization statistics of any connected storage device, presented in a straightforward graphical format that is understandable for both technicians and management. By introducing a user-friendly solution, it facilitates improved capacity planning for your highly virtualized environment. The Stor2RRD tool effectively delivers insights on performance, capacity, configuration, and overall status. This enables swift identification of load irregularities and assists in pinpointing issues at the infrastructure level, ultimately leading to a more efficient operational framework.

Salesforce Data Cloud serves as a real-time data platform aimed at consolidating and overseeing customer information from diverse sources within a business, facilitating a unified and thorough perspective of each client. This platform empowers organizations to gather, synchronize, and evaluate data in real time, thereby creating a complete 360-degree customer profile that can be utilized across various Salesforce applications, including Marketing Cloud, Sales Cloud, and Service Cloud. By merging data from both online and offline avenues, such as CRM data, transactional records, and external data sources, it fosters quicker and more personalized interactions with customers. Additionally, Salesforce Data Cloud is equipped with sophisticated AI tools and analytical features, enabling businesses to derive deeper insights into customer behavior and forecast future requirements. By centralizing and refining data for practical application, it enhances customer experiences, allows for targeted marketing efforts, and promotes effective, data-driven decisions throughout different departments. Ultimately, Salesforce Data Cloud not only streamlines data management but also plays a crucial role in helping organizations stay competitive in a rapidly evolving marketplace.

The Azure Marketplace serves as an extensive digital storefront, granting users access to a vast array of certified, ready-to-use software applications, services, and solutions provided by both Microsoft and various third-party vendors. This platform allows businesses to easily explore, purchase, and implement software solutions directly within the Azure cloud ecosystem. It features a diverse selection of products, encompassing virtual machine images, AI and machine learning models, developer tools, security features, and applications tailored for specific industries. With various pricing structures, including pay-as-you-go, free trials, and subscriptions, Azure Marketplace makes the procurement process more straightforward and consolidates billing into a single Azure invoice. Furthermore, its seamless integration with Azure services empowers organizations to bolster their cloud infrastructure, streamline operational workflows, and accelerate their digital transformation goals effectively. As a result, businesses can leverage cutting-edge technology solutions to stay competitive in an ever-evolving market.

As a leader in the business arena, it's crucial to have unwavering confidence in your data, ensuring it is thoroughly governed, compliant, and precise. This entails incorporating all data from every source and location without any restrictions. It's important to have a comprehensive grasp of your data resources. Conduct audits to assess risks, compliance, and quality to support your initiatives. Create a detailed inventory of data across all sources and types, fostering a collective understanding of your data resources. Execute a swift, cost-effective, and precise one-time audit of your data assets. Audits for PCI, PII, and PHI are designed to be both fast and thorough. This service approach eliminates the need for any software purchases. Evaluate and audit the quality and duplication of data within all your enterprise data assets, whether they are cloud-native or on-premises. Ensure compliance with global data privacy regulations on a large scale. Actively discover, classify, track, trace, and audit compliance with privacy standards. Additionally, oversee the propagation of PII, PCI, and PHI data while automating the processes for complying with Data Subject Access Requests (DSAR). This comprehensive strategy will effectively safeguard your data integrity and enhance overall business operations.