Best Data Virtualization Software in Japan - Page 2

Accelerate AI innovation with cloud-native data integration on IBM Cloud Pak for data. AI-powered data integration, anywhere. Your AI and analytics are only as good as the data that fuels them. With a modern container-based architecture, IBM® DataStage® for IBM Cloud Pak® for Data delivers that high-quality data. It combines industry-leading data integration with DataOps, governance and analytics on a single data and AI platform. Automation accelerates administrative tasks to help reduce TCO. AI-based design accelerators and out-of-the-box integration with DataOps and data science services speed AI innovation. Parallelism and multicloud integration let you deliver trusted data at scale across hybrid or multicloud environments. Manage the data and analytics lifecycle on the IBM Cloud Pak for Data platform. Services include data science, event messaging, data virtualization and data warehousing. Parallel engine and automated load balancing.

There are many products on the market that can help companies to do this, but if your priorities are to create a data-driven enterprise and to be as efficient and cost-effective as possible, then there is only one solution you should consider: Fraxses, the world’s foremost distributed data platform. Fraxses provides customers with access to data on demand, delivering powerful insights via a solution that enables a data mesh or data fabric architecture. Think of a data mesh as a structure that can be laid over disparate data sources, connecting them, and enabling them to function as a single environment. Unlike other data integration and virtualization platforms, the Fraxses data platform has a decentralized architecture. While Fraxses fully supports traditional data integration processes, the future lies in a new approach, whereby data is served directly to users without the need for a centrally owned data lake or platform.

Varada’s dynamic and adaptive big data indexing solution enables to balance performance and cost with zero data-ops. Varada’s unique big data indexing technology serves as a smart acceleration layer on your data lake, which remains the single source of truth, and runs in the customer cloud environment (VPC). Varada enables data teams to democratize data by operationalizing the entire data lake while ensuring interactive performance, without the need to move data, model or manually optimize. Our secret sauce is our ability to automatically and dynamically index relevant data, at the structure and granularity of the source. Varada enables any query to meet continuously evolving performance and concurrency requirements for users and analytics API calls, while keeping costs predictable and under control. The platform seamlessly chooses which queries to accelerate and which data to index. Varada elastically adjusts the cluster to meet demand and optimize cost and performance.

Hammerspace is a revolutionary storage platform that unlocks unused local NVMe storage in GPU servers to accelerate AI training and checkpointing. It transforms siloed, stranded storage into a shared, ultra-fast tier that dramatically increases GPU utilization and reduces the need for costly external storage systems. By using a standards-based parallel file system, Hammerspace delivers low-latency, high-throughput data access that scales to thousands of GPU servers. The platform helps cut power consumption and infrastructure costs while boosting AI workload performance. Leading organizations like Meta rely on Hammerspace to optimize their AI infrastructure. With easy deployment and rapid scaling, Hammerspace enables teams to get AI models trained faster and more efficiently.

Red Hat JBoss Data Virtualization is a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. Red Hat JBoss Data Virtualization makes data spread across physically diverse systems, such as multiple databases, XML files, and Hadoop systems, appear as a set of tables in a local database. Provides standards-based read/write access to heterogeneous data stores in real-time. Speeds application development and integration by simplifying access to distributed data. Integrate and transform data semantics based on data consumer requirements. Provides centralized access control, and auditing through robust security infrastructure. Turn fragmented data into actionable information at the speed your business needs. Red Hat offers support and maintenance over stated time periods for the major versions of JBoss products.

Traditional methods of integrating mainframe data, ETL, data warehouses, building connectors, are simply not fast, accurate, or efficient enough for business today. More data than ever before is being created and stored on the mainframe, leaving these old methods further behind. Only data virtualization can close the ever-widening gap to automate the process of making mainframe data broadly accessible to developers and applications. You can curate (discover and map) your data once, then virtualize it for use anywhere, again and again. Finally, your data scales to your business ambitions. Data virtualization on z/OS eliminates the complexity of working with mainframe resources. Using data virtualization, you can knit data from multiple, disconnected sources into a single logical data source, making it much easier to connect mainframe data with your distributed applications. Combine mainframe data with location, social media, and other distributed data.

TIBCO delivers industrial-strength solutions that meet your performance, throughput, reliability, and scalability needs while offering a wide range of technology and deployment options to deliver real-time data where it’s needed most. The TIBCO Platform will bring together an evolving set of your TIBCO solutions wherever they are hosted—in the cloud, on-premises, and at the edge—into a single, unified experience so that you can more easily manage and monitor them. TIBCO helps build solutions that are essential to the success of the world’s largest enterprises.

Rocket DataEdge is a comprehensive, unified data integration platform that discovers, accesses, manages, and secures enterprise data across transactional, distributed, and cloud environments to make data decision-ready for AI, analytics, and applications. It integrates core systems, including IBM Z and IBM i, with on-premises and cloud targets using high-performance, vendor-agnostic connectors and log-based, bi-directional change data capture with transactional fidelity and schema evolution to keep sources and targets in sync for trusted, real-time governed data. DataEdge automates metadata scanning, cataloging, lineage, and semantic views to enable governed self-service discovery and clear data relevance, driving faster access and use of the right data. It supports data virtualization and federation with federated query (SQL/REST), pushdown optimization, and caching to activate data without extra copies.

It unifies information across silos and scattered data for visibility across multiple sources in a single environment; whether in the cloud, spread across siloed databases, on instruments, in Big Data stores, or within various spreadsheets/documents, Enterprise Enabler can integrate all your data so you can make informed business decisions in real-time. By creating logical views of data from the original source locations. This means you can reuse, configure, test, deploy, and monitor all your data in a single integrated environment. Analyze your business data in one place as it is occurring to maximize the use of assets, minimize costs, and improve/refine your business processes. Our implementation time to market value is 50-90% faster. We get your sources connected and running so you can start making business decisions based on real-time data.

The core technology to enable modern data integration and data management solutions. Quickly connect disparate structured and unstructured sources. Catalog your entire data ecosystem. Data stays in the sources and it is accessed on demand, with no need to create another copy. Build data models that suit the needs of the consumer, even across multiple sources. Hide the complexity of your back-end technologies from the end users. The virtual model can be secured and consumed using standard SQL and other formats like REST, SOAP and OData. Easy access to all types of data. Full data integration and data modeling capabilities. Active Data Catalog and self-service capabilities for data & metadata discovery and data preparation. Full data security and data governance capabilities. Fast intelligent execution of data queries. Real-time data delivery in any format. Ability to create data marketplaces. Decoupling of business applications from data systems to facilitate data-driven strategies.

For ERPs like Oracle e-Business Suite, PeopleSoft & Databases Clonetab is the only software which can virtualize and provide true end-to-end on-demand clones of ERPs (like Oracle e-Business Suite, PeopleSoft) or databases. It can also provide an integrated solution for virtualization, cloning, Disaster Recovery, Backups and Oracle EBS Snapshots. Clonetab engines – Deeply aware of ERP Applications, not just Databases The engines are deeply EBS & PS aware and can identify the major releases (e.g. R12.1, R12.2) and patchset levels like AD, TXK and executes the clone commands accordingly. The platform provides options to retain EBS/PS specific options like profile option retention, Concurrent/Process scheduler setups retention, EBS users with responsibilities retention, Database links, Directories retention, workflows setups and many more options, resulting in a true end-to-end ERP clone.

Real-time monitoring and alarming of measured rain using rain gauges to alert or trigger operations staff of specific flooding or sewer overflow potential. Monitoring and analyzing the rainfall amounts in various locations to assess the amount of rain in other non-monitored locations also referred to as the “Distributed Rainfall Modelling Technique” (DRMT). Analysis of rainfall radar data in combination with rain gauge rainfall data to produce improved rainfall coverage maps. Analysis of recent rainfall records to develop rainfall intensity-duration curves for comparing with the area’s design intensity-duration-frequency curves and define the return periods of observed events (forensic analysis). Develop new intensity-duration-frequency curves for designing drainage system infrastructure (sewers, channels, storage facilities). Flow monitoring and data analysis to develop rainfall versus stormwater runoff response curves for calibrating drainage system models.

Dremio delivers lightning-fast queries and a self-service semantic layer directly on your data lake storage. No moving data to proprietary data warehouses, no cubes, no aggregation tables or extracts. Just flexibility and control for data architects, and self-service for data consumers. Dremio technologies like Data Reflections, Columnar Cloud Cache (C3) and Predictive Pipelining work alongside Apache Arrow to make queries on your data lake storage very, very fast. An abstraction layer enables IT to apply security and business meaning, while enabling analysts and data scientists to explore data and derive new virtual datasets. Dremio’s semantic layer is an integrated, searchable catalog that indexes all of your metadata, so business users can easily make sense of your data. Virtual datasets and spaces make up the semantic layer, and are all indexed and searchable.