Best Big Data Platforms in China - Page 8

bi(OS)® offers an unmatched speed to insight for developers of data applications in a cohesive manner. With bi(OS)®, the entire process of creating data applications can be completed in just a matter of hours to days. This comprehensive approach encompasses the integration of diverse data sources, the extraction of real-time insights, and the smooth deployment into production environments. By joining forces with enterprise data teams across various sectors, you can transform into the data superhero your organization needs. The combination of Open Source, Cloud, and SaaS has not fulfilled its potential for delivering genuine data-driven results. Enterprises have largely focused their investments on data movement and integration, a strategy that is ultimately unsustainable. A fresh perspective on data management is urgently required, one that considers the unique challenges of enterprises. bi(OS)® is designed by rethinking fundamental principles in enterprise data management, ranging from data ingestion to insight generation. It caters to the needs of API, AI, and BI developers in a cohesive manner, enabling data-driven outcomes within days. As engineers collaborate effectively, a harmonious relationship emerges among IT teams, tools, and processes, creating a lasting competitive advantage for the organization.

EMR allows you to adjust the size of your managed Hadoop clusters either manually or automatically, adapting to your business needs and monitoring indicators. Its architecture separates storage from computation, which gives you the flexibility to shut down a cluster to optimize resource utilization effectively. Additionally, EMR features hot failover capabilities for CBS-based nodes, utilizing a primary/secondary disaster recovery system that enables the secondary node to activate within seconds following a primary node failure, thereby ensuring continuous availability of big data services. The metadata management for components like Hive is also designed to support remote disaster recovery options. With computation-storage separation, EMR guarantees high data persistence for COS data storage, which is crucial for maintaining data integrity. Furthermore, EMR includes a robust monitoring system that quickly alerts you to cluster anomalies, promoting stable operations. Virtual Private Clouds (VPCs) offer an effective means of network isolation, enhancing your ability to plan network policies for managed Hadoop clusters. This comprehensive approach not only facilitates efficient resource management but also establishes a reliable framework for disaster recovery and data security.

Apache Arrow establishes a columnar memory format that is independent of any programming language, designed to handle both flat and hierarchical data, which allows for optimized analytical processes on contemporary hardware such as CPUs and GPUs. This memory format enables zero-copy reads, facilitating rapid data access without incurring serialization delays. Libraries associated with Arrow not only adhere to this format but also serve as foundational tools for diverse applications, particularly in high-performance analytics. Numerous well-known projects leverage Arrow to efficiently manage columnar data or utilize it as a foundation for analytic frameworks. Developed by the community for the community, Apache Arrow emphasizes open communication and collaborative decision-making. With contributors from various organizations and backgrounds, we encourage inclusive participation in our ongoing efforts and developments. Through collective contributions, we aim to enhance the functionality and accessibility of data analytics tools.

Hypertable provides a high-performance, scalable database solution that enhances the efficiency of your big data applications while minimizing hardware usage. This platform offers exceptional efficiency and outperforms its competitors, leading to significant cost reductions for users. Its robust and proven architecture supports numerous services at Google. Users can enjoy the advantages of open-source technology backed by a vibrant and active community. With a C++ implementation, Hypertable ensures optimal performance. Additionally, it offers around-the-clock support for critical big data operations. Clients benefit from direct access to the expertise of the core developers behind Hypertable. Specifically engineered to address scalability challenges that traditional relational database management systems struggle with, Hypertable leverages a design model pioneered by Google to effectively tackle scaling issues, making it superior to other NoSQL alternatives available today. Its innovative approach not only resolves current scalability needs but also anticipates future demands in data management.

Utilize widely-used open-source frameworks like Apache Hadoop, Spark, Hive, and Kafka with Azure HDInsight, a customizable and enterprise-level service designed for open-source analytics. Effortlessly manage vast data sets while leveraging the extensive open-source project ecosystem alongside Azure’s global capabilities. Transitioning your big data workloads to the cloud is straightforward and efficient. You can swiftly deploy open-source projects and clusters without the hassle of hardware installation or infrastructure management. The big data clusters are designed to minimize expenses through features like autoscaling and pricing tiers that let you pay solely for your actual usage. With industry-leading security and compliance validated by over 30 certifications, your data is well protected. Additionally, Azure HDInsight ensures you remain current with the optimized components tailored for technologies such as Hadoop and Spark, providing an efficient and reliable solution for your analytics needs. This service not only streamlines processes but also enhances collaboration across teams.

Break down data silos through a unified storage solution that effectively optimizes expenses by employing tiered storage and comprehensive policy management. Enhance data authentication with Azure Active Directory (Azure AD) alongside role-based access control (RBAC), while bolstering data protection with features such as encryption at rest and advanced threat protection. This approach ensures a highly secure environment with adaptable mechanisms for safeguarding access, encryption, and network-level governance. Utilizing a singular storage platform, you can seamlessly ingest, process, and visualize data while supporting prevalent analytics frameworks. Cost efficiency is further achieved through the independent scaling of storage and compute resources, lifecycle policy management, and object-level tiering. With Azure's extensive global infrastructure, you can effortlessly meet diverse capacity demands and manage data efficiently. Additionally, conduct large-scale analytical queries with consistently high performance, ensuring that your data management meets both current and future needs.

Harness the power of your data and create innovative artificial intelligence (AI) solutions using Azure Databricks, where you can establish your Apache Spark™ environment in just minutes, enable autoscaling, and engage in collaborative projects within a dynamic workspace. This platform accommodates multiple programming languages such as Python, Scala, R, Java, and SQL, along with popular data science frameworks and libraries like TensorFlow, PyTorch, and scikit-learn. With Azure Databricks, you can access the most current versions of Apache Spark and effortlessly connect with various open-source libraries. You can quickly launch clusters and develop applications in a fully managed Apache Spark setting, benefiting from Azure's expansive scale and availability. The clusters are automatically established, optimized, and adjusted to guarantee reliability and performance, eliminating the need for constant oversight. Additionally, leveraging autoscaling and auto-termination features can significantly enhance your total cost of ownership (TCO), making it an efficient choice for data analysis and AI development. This powerful combination of tools and resources empowers teams to innovate and accelerate their projects like never before.

Varada offers a cutting-edge big data indexing solution that adeptly balances performance and cost while eliminating the need for data operations. This distinct technology acts as an intelligent acceleration layer within your data lake, which remains the central source of truth and operates within the customer's cloud infrastructure (VPC). By empowering data teams to operationalize their entire data lake, Varada facilitates data democratization while ensuring fast, interactive performance, all without requiring data relocation, modeling, or manual optimization. The key advantage lies in Varada's capability to automatically and dynamically index pertinent data, maintaining the structure and granularity of the original source. Additionally, Varada ensures that any query can keep pace with the constantly changing performance and concurrency demands of users and analytics APIs, while also maintaining predictable cost management. The platform intelligently determines which queries to accelerate and which datasets to index, while also flexibly adjusting the cluster to match demand, thereby optimizing both performance and expenses. This holistic approach to data management not only enhances operational efficiency but also allows organizations to remain agile in an ever-evolving data landscape.

Doolytic is at the forefront of big data discovery, integrating data exploration, advanced analytics, and the vast potential of big data. The company is empowering skilled BI users to participate in a transformative movement toward self-service big data exploration, uncovering the inherent data scientist within everyone. As an enterprise software solution, doolytic offers native discovery capabilities specifically designed for big data environments. Built on cutting-edge, scalable, open-source technologies, doolytic ensures lightning-fast performance, managing billions of records and petabytes of information seamlessly. It handles structured, unstructured, and real-time data from diverse sources, providing sophisticated query capabilities tailored for expert users while integrating with R for advanced analytics and predictive modeling. Users can effortlessly search, analyze, and visualize data from any format and source in real-time, thanks to the flexible architecture of Elastic. By harnessing the capabilities of Hadoop data lakes, doolytic eliminates latency and concurrency challenges, addressing common BI issues and facilitating big data discovery without cumbersome or inefficient alternatives. With doolytic, organizations can truly unlock the full potential of their data assets.

Effortlessly leverage your entire system's data with our SHREWD Platform, which features advanced tools and open APIs. The SHREWD Platform is equipped with integration and data collection tools that support the operations of various SHREWD modules. These tools consolidate data and securely store it in a UK-based data lake. Subsequently, the data can be accessed by SHREWD modules or through an API, allowing for the transformation of raw information into actionable insights tailored to specific needs. The platform can ingest data in virtually any format, whether it’s in traditional spreadsheets or through modern digital systems via APIs. Additionally, the system’s open API facilitates third-party connections, enabling external applications to utilize the information stored in the data lake when necessary. By providing an operational data layer that serves as a real-time single source of truth, the SHREWD Platform empowers its modules to deliver insightful analytics, enabling managers and decision-makers to act promptly and effectively. This holistic approach to data management ensures that organizations can remain agile and responsive to changing demands.

IBM Sterling Fulfillment Optimizer powered by Watson is an advanced cognitive analytics platform that significantly improves the functionality of current order management systems. This innovative solution serves as a "big data brain," providing enhanced order management and inventory visibility for retailers involved in eCommerce fulfillment. By leveraging Fulfillment Optimizer, retailers gain deeper insights and can respond promptly to market fluctuations, allowing them to strike an ideal balance between maintaining profit margins, optimizing store capacity, and fulfilling delivery commitments. The informed sourcing decisions made possible by this tool can lead to substantial profit increases, particularly during high-demand periods. Additionally, it enables retailers to assess the ramifications of omnichannel strategies across various sectors including eCommerce, merchandising, logistics, store operations, and supply chain management. By smartly balancing the costs associated with omnichannel fulfillment against service quality, retailers can safeguard their profit margins while maximizing the utilization of store capacity and ensuring timely deliveries to customers. Furthermore, the platform simplifies the execution of optimized omnichannel fulfillment strategies, ensuring the lowest possible cost of service while meeting customer expectations effectively.

IBM® Sterling Transformation Extender empowers organizations to seamlessly integrate transactions involving customers, suppliers, and business partners across their entire operations. This tool automates the intricate processes of data transformation and validation, accommodating a wide array of formats and standards. Users can execute data transformations in both on-premises settings and cloud environments. Furthermore, it offers advanced transformation capabilities that include metadata for mapping, compliance verification, and related processing functionalities tailored to specific sectors, such as finance, healthcare, and supply chain management. The system supports both structured and unstructured data, along with custom formats, and is compatible with on-premises, hybrid, private, and public cloud configurations. With a strong focus on user experience, it features RESTful APIs for enhanced functionality. The solution facilitates complex transformations and validation of data across multiple formats, enabling any-to-any data transformation while being containerized for cloud deployment. Additionally, it includes industry-specific packs to further streamline operations and enhance efficiency.

Leverage cutting-edge, actionable analytics to enhance your manufacturing effectiveness, speed up the introduction of new products, and simultaneously improve their reliability. By utilizing the foremost big data analytics platform and years of specialized knowledge, you can elevate the efficiency, quality, and dependability of your manufacturing processes. Furthermore, gain crucial insights into your supply chain while maximizing manufacturing performance and accelerating the product development cycle. As a lifecycle analytics firm, we empower automotive and semiconductor manufacturers to fully utilize their data. Our innovative open platform is meticulously crafted for your sector, offering an in-depth understanding of all product attributes and fostering innovation through a holistic end-to-end solution that incorporates advanced analytics, artificial intelligence, and machine learning, setting the foundation for future advancements. This comprehensive approach ensures that you not only stay competitive but also lead in your industry.

As interactions with customers increasingly transition from physical to digital environments, it becomes necessary to move beyond traditional face-to-face conversations. Instead, customers now convey their preferences and requirements through data. Gaining insights into customer behavior and validating our preconceptions about them also relies heavily on data-driven approaches. However, stringent privacy laws like GDPR and CCPA complicate this deep understanding even further. The MOSTLY AI synthetic data platform effectively addresses this widening gap in customer insights. This reliable and high-quality synthetic data generator supports businesses across a range of applications. Offering privacy-compliant data alternatives is merely the starting point of its capabilities. In terms of adaptability, MOSTLY AI's synthetic data platform outperforms any other synthetic data solution available. The platform's remarkable versatility and extensive use case applicability establish it as an essential AI tool and a transformative resource for software development and testing. Whether for AI training, enhancing explainability, mitigating bias, ensuring governance, or generating realistic test data with subsetting and referential integrity, MOSTLY AI serves a broad spectrum of needs. Ultimately, its comprehensive features empower organizations to navigate the complexities of customer data while maintaining compliance and protecting user privacy.

Currently, less than 10% of the vast $260 billion big data industry is being utilized, primarily due to outdated processes and the overpowering presence of intermediaries. Our goal is to democratize this market, enabling access to the remaining 90% of data that is currently untapped for sharing. We aim to establish a decentralized framework that creates a data oracle network, utilizing an open protocol that facilitates interaction among participants while fostering a sustainable economy. Our multifunctional decentralized application (DAPP) and crypto wallet provide users with the opportunity to earn rewards for the data they generate, alongside access to various decentralized finance (DeFi) tools through a seamless user experience. The GeoDB marketplace empowers data buyers globally to acquire data produced by users through applications linked to the GeoDB platform. Participants, known as data sources, contribute data that is uploaded via our proprietary and partner applications, while validators ensure the efficient transfer and verification of contracts through blockchain technology, allowing for a streamlined and decentralized process. This innovative approach not only enhances data accessibility but also promotes a collaborative environment for all stakeholders involved.

A framework for distributed data integration that streamlines essential functions of Big Data integration, including data ingestion, replication, organization, and lifecycle management, is designed for both streaming and batch data environments. It operates as a standalone application on a single machine and can also function in an embedded mode. Additionally, it is capable of executing as a MapReduce application across various Hadoop versions and offers compatibility with Azkaban for initiating MapReduce jobs. In standalone cluster mode, it features primary and worker nodes, providing high availability and the flexibility to run on bare metal systems. Furthermore, it can function as an elastic cluster in the public cloud, maintaining high availability in this setup. Currently, Gobblin serves as a versatile framework for creating various data integration applications, such as ingestion and replication. Each application is usually set up as an independent job and managed through a scheduler like Azkaban, allowing for organized execution and management of data workflows. This adaptability makes Gobblin an appealing choice for organizations looking to enhance their data integration processes.

Streamlined distributed computing significantly enhances graph-analytics performance without requiring extensive infrastructure changes. By incorporating a broader variety of data for standardization and visualization on the graph, insights can be significantly strengthened. The combination of advancements in both graph and deep learning results in efficiencies that facilitate prompt insights on the largest graphs in existence. Katana Graph equips Financial Services firms with the tools to tap into the vast possibilities offered by graph analytics and AI at scale, enabling everything from real-time fraud detection to comprehensive customer insights. Leveraging breakthroughs in high-performance parallel computing (HPC), Katana Graph’s intelligent platform evaluates risks and uncovers customer insights from massive data sets using rapid analytics and AI capabilities that surpass those of alternative graph technologies. This transformative approach allows organizations to stay ahead of trends and make data-driven decisions with confidence.

Introducing a cutting-edge cloud-native platform for Decision Automation that utilizes AI to create tailored solutions for various use cases. Incedo LighthouseTM taps into AI's capabilities within a low-code framework to provide daily insights and actionable recommendations by harnessing the speed and power of Big Data. By optimizing customer experiences and offering highly personalized recommendations, Incedo LighthouseTM helps enhance your revenue potential significantly. Our AI and machine learning-driven models facilitate personalization throughout the entire customer journey. Additionally, Incedo LighthouseTM contributes to cost reduction by streamlining the processes of problem identification, insight generation, and the execution of focused actions. The platform features advanced machine learning for metric monitoring and root cause analysis, ensuring it effectively oversees the quality of large-scale data loads. By leveraging AI and ML to address quality issues, Incedo LighthouseTM enhances data reliability, fostering greater confidence among users in their data-driven decisions. Ultimately, this platform represents a transformative solution for organizations aiming to leverage technology for improved decision-making and operational efficiency.

Somnoware’s sleep lab management software empowers you to diagnose and manage patients according to your preferences, utilizing any major testing device available. It consolidates PAP data into a single, secure platform while automating patient engagement and allowing for customizable dashboards and reports, ensuring all your needs are met in one location. The Diagnostic Module from Somnoware streamlines the execution of diagnostic tests, making scheduling effortless, keeping inventory active, and providing physicians with immediate access to test results, with therapy orders just a click away. Additionally, Somnoware Diagnostics operates on a cloud-based system that enhances the management of respiratory and sleep care, facilitating data integration from various medical devices, which leads to quicker screenings and diagnoses, ultimately resulting in better treatment outcomes. Adhering to the SOC 2 security framework, which aligns with HIPAA and GDPR compliance, further demonstrates our unwavering commitment to safeguarding your data. This combination of advanced technology and strict security measures positions Somnoware as a leader in the field of sleep lab management.

Rolta is at the forefront of digital transformation, providing innovative IP-based solutions. The Rolta OneView™ platform, which has received numerous accolades, is the result of over thirty years of expertise in engineering, geospatial, IT, and analytics. Rolta presents an all-encompassing Business Intelligence and Big Data analytics solution designed to help organizations achieve both operational and business excellence. Companies in asset-intensive sectors gain immediate business benefits from the solution's role-specific actionable insights, a library of more than 3000 pre-built analytics tailored to various industries, established knowledge models, and an architecture that ensures cross-functional performance integrity. The Rolta OneView™ Enterprise Suite delivers distinctive business advantages through its role-focused actionable insights, aligning operational and business intelligence for strategic organizational impact. By leveraging this comprehensive suite, organizations can make well-informed decisions that pave the way for meaningful business transformation and success in a competitive landscape.

A mobile-based portal enhanced with third-party data offers the capability to: — reconstruct the sociodemographic profiles of users, including attributes like gender and age, — create distinct user segments such as young parents, frequent travelers, blue-collar workers, university students, and affluent residents, — deliver analytics tailored to client specifications, addressing factors like user concentration in specific areas, customer loyalty, emerging trends, variations, and competitive comparisons, — identify optimal sites for establishing new kindergartens, supermarkets, or malls based on concentrations of users, their interests, and sociodemographic characteristics. Initially developed as a bespoke solution for a client in the UAE, this offering has evolved into a comprehensive product in response to increasing demand, assisting various businesses in tackling crucial challenges and answering significant queries such as: — initiating highly targeted advertising campaigns, — discovering the most advantageous locations for new business establishments, — pinpointing ideal spots for outdoor advertising displays, and significantly enhancing strategic planning efforts.

Data-driven organizations, regardless of their preparedness, face significant challenges stemming from the ever-increasing volume, speed, and diversity of data. As the demand for advanced analytics intensifies, the limitations of infrastructure, time, and human resources become more pronounced. Xurmo effectively addresses these challenges with its user-friendly, self-service platform. Users can configure and ingest any type of data through a single interface effortlessly. Whether dealing with structured or unstructured data, Xurmo seamlessly incorporates it into the analysis process. Allow Xurmo to handle the heavy lifting so you can focus on configuring intelligent solutions. From developing analytical models to deploying them in an automated fashion, Xurmo provides interactive support throughout the journey. Furthermore, it enables the automation of intelligence derived from even the most intricate, rapidly changing datasets. With Xurmo, analytical models can be both customized and deployed across various data environments, ensuring flexibility and efficiency in the analytics process. This comprehensive solution empowers organizations to harness their data effectively, transforming challenges into opportunities for insight.

We are MotherDuck, a dynamic software company created by a dedicated group of seasoned data enthusiasts. Our team has held leadership roles in some of the most prestigious data organizations. Instead of focusing on costly and sluggish scale-out solutions, we propose a scale-up approach. The era of Big Data is behind us; it’s time for the era of easy data to take the lead. Your laptop outperforms your data warehouse, so why should you have to wait for the cloud? DuckDB has proven its worth, so let’s enhance its capabilities. When we established MotherDuck, we saw DuckDB as a potential revolutionary tool due to its user-friendliness, portability, incredible speed, and the swift evolution driven by its community. At MotherDuck, our mission is to support the community, the DuckDB Foundation, and DuckDB Labs in enhancing the recognition and adoption of DuckDB, catering to users who prefer local work or desire a serverless, always-on SQL execution method. Our exceptional team comprises engineers and leaders with extensive backgrounds in databases and cloud technologies from industry giants such as AWS, Databricks, Elastic, Facebook, Firebolt, Google BigQuery, Neo4j, SingleStore, and many others. We believe that with the right tools and community, the future of data management can be redefined for everyone.

MUSO is a world leading data company that provides anti-piracy protection and audience measurement. MUSO Protect is our market leading automated content protection technology which protects content for some of the world’s largest rights holders in the media industry. MUSO Discover is our unique audience demand platform. MUSO Discover measures demand across the piracy ecosystem, enabling rights holders to see the true demand for their content that is unbiased and unrestricted by region or platform. Unlicensed demand data allows content owners to increase the value of content for distribution, discover in-demand titles for acquisition, discover popularity trends for content commission and analyse windowing impact strategies.

At Vaex.io, our mission is to make big data accessible to everyone, regardless of the machine or scale they are using. By reducing development time by 80%, we transform prototypes directly into solutions. Our platform allows for the creation of automated pipelines for any model, significantly empowering data scientists in their work. With our technology, any standard laptop can function as a powerful big data tool, eliminating the need for clusters or specialized engineers. We deliver dependable and swift data-driven solutions that stand out in the market. Our cutting-edge technology enables the rapid building and deployment of machine learning models, outpacing competitors. We also facilitate the transformation of your data scientists into proficient big data engineers through extensive employee training, ensuring that you maximize the benefits of our solutions. Our system utilizes memory mapping, an advanced expression framework, and efficient out-of-core algorithms, enabling users to visualize and analyze extensive datasets while constructing machine learning models on a single machine. This holistic approach not only enhances productivity but also fosters innovation within your organization.