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Cisco Integrated Infrastructure for Big Data and Analytics with Vertica Advanced Analytics Platform Solution Overview Cisco Integrated Infrastructure for Big Data and Analytics with Vertica Advanced Analytics Platform Highlights Proven enterprise-ready converged Advanced analytics engine data platform • The Vertica Advanced Analytics Platform is • Cisco UCS® Integrated Infrastructure for Big designed from the foundation as a massively Data and Analytics offers complete integration of parallel, cluster-aware columnar SQL analytical computing, networking, and storage resources database. It can be installed natively as a database with unified management and provides high or directly on Apache Hadoop as a query engine. performance, expandable storage, and scalable, The unique architecture supports simultaneous advanced analytics with Vertica. load and query operations with high availability, compression, and more. Built on the Cisco Unified Computing System™ (Cisco UCS) Actionable insights on database layer • The solution uses a fabric-centric architecture, • With machine learning built directly into the core providing business acceleration, a true on-demand of Vertica (in-database machine learning), and with infrastructure, and a system that grows gracefully many SQL analytics functions for data preparation, and incrementally. Vertica is excellent for anomaly detection, predictive maintenance, smart manufacturing, and Designed, tested, and validated for faster deep analysis of massive amounts of data. time to value • Prevalidation through industry-standard ANSI SQL–compliant structured SQL interface benchmarks, tighter integration, and • Vertica is ANSI SQL compliant and tightly performance optimization reduce integration integrates with a wide range of business and deployment risk and provide more intelligence and Extract, Transform, and Load (ETL) predictable customer deployments. tools. It supports the Hadoop framework, with optimized support for queries on Parquet, ORC, JSON, and Avro files. Cisco Integrated Infrastructure for Big Data and Analytics with Vertica Advanced Analytics Platform | Solution Overview Service-Level Agreement (SLA) based Actionable insights provide Reliability, Availability, and Scalability (RAS) for analytics greater value Built by design to dramatically improve query • The solution has no single point of failure. The performance over traditional relational database Vertica analytical database responds appropriately systems, Vertica is purpose built with in-database if a node or disk drive fails. advanced analytics capabilities that are fine-tuned to • Vertica includes both a proprietary highly optimized handle a range of complex big data queries. At the format and support for optimized Hadoop formats. base of Vertica is the insight achieved with a fast SQL Users can meet even the most demanding SLAs by analytical database. The Vertica Advanced Analytics analyzing the data in place. Platform supports ANSI SQL standards and augments SQL with geospatial, time-series analytics, data- Real-time big data analytics platforms preparation functions, live aggregation, and custom in the modern data center analytics. In addition, you can perform supervised In today’s highly competitive business environment, and unsupervised Machine Learning using popular where nearly every industry is experiencing algorithms such as linear regression, logistic regression, transformation and disruption, change is constant. k-means, Naïve Bayes, and support vector machine Maintaining a competitive advantage requires data- (SVM). You don’t have to move data out of the database driven organizations to think differently and develop to achieve all the insights you need. You can use new core competencies derived from analytical the power of Vertica’s optimizations to move quickly insight. Success and growth have become intrinsically through analytics: both descriptive and predictive. linked with machine learning for predictive analytics. These unique capabilities enable actionable insight As companies collect and rely on data more and remediation: the capability to engage and frequently, the velocity, variety, and volume of data take action based on information while it maintains sources evolves daily. This continuous change creates relevance and value. Vertica customers separate greater complexity and scale that traditional systems, themselves from their competitors by producing and even newer open-source systems, either were not value from petabytes of data and beyond. designed to handle or have not yet been proven to handle in real-world, unforgiving environments with stringent Service-Level Agreements (SLAs). While Bringing Apache Hadoop data alive organizations are grappling with these challenges with analytics and market demands, a new trend has emerged in Many companies have chosen to use Apache Hadoop which data is the “new oil,” and information and to store massive volumes of unstructured data, insights from this data is the “new gold.” As industry but performing analytics processing on Hadoop markets have demonstrated, generous valuations and workloads can be challenging. Because Hadoop financial success are often rewarded to organizations is not a database, it can be challenging to handle capable of monetizing business data now—not after concurrent queries or gain access to all the insights the opportunity has passed. you need. If you apply the right set of SQL to Hadoop data analytics capabilities, you can dramatically Real-time analytics is becoming a fundamental reduce complexity and accelerate time to insight. differentiator in all industry markets: for instance, predictive maintenance for the Internet of Things At the same time that Hadoop is being used for (IoT), risk management for banking, fraud detection persistent storage, Enterprise Data Warehouses for e-retail, and predictive analytics for customer (EDWs) are growing in size and complexity due to retention and uplift. And modern systems need to rapidly changing data requirements. The increase in support the most demanding analytics initiatives data complexity and heightened demand for access and adapt to big data strategies as business from business stakeholders places a burden on EDWs demands change. to support increasing numbers of data consumers. New data sources from IoT sensors, mobile and online applications, and machine-generated sources such as web and application logs place a burden Cisco Integrated Infrastructure for Big Data and Analytics with Vertica Advanced Analytics Platform | Solution Overview 2 on both the data warehouse and the Hadoop and advanced analytics, offer a tightly integrated environments. These requirements create a burden solution that helps data-driven organizations identify that the solutions were not designed to handle. trends and predict behaviors. The power of Cisco UCS and Vertica comes from the capability to deliver Another aspect of the data deluge challenge is advanced, complex analytics to a broad universe of economics. Data lakes based on Hadoop offer users on any device, promoting the democratization economical alternatives for data ill-suited for the of data and analytics everywhere. EDW. Although the data warehouse is well-suited for mixed analytical workloads, the data lake can support many of the functions of the EDW, but Cisco UCS Integrated Infrastructure with less support for concurrency and fixed SLAs. for Big Data and Analytics Information lifecycle management is on the collective Organizations today must help ensure that the minds of many organizations as they seek to keep hot underlying physical infrastructure can be deployed, data hot and less frequently queried data in a more scaled, and managed in a way that is agile enough economical storage location. To increase adoption to change as workloads and business requirements and distribution of these projects, data lakes need change. Cisco UCS Integrated Infrastructure for to support SQL-based tools to provide business Big Data and Analytics has redefined the potential stakeholders with direct access. of the data center with its revolutionary approach to managing computing, network, and storage Vertica recognizes these market conditions. In resources to successfully address the business addition to being deployed as a Linux-based needs of IT innovation and acceleration. Cisco UCS database, Vertica can be deployed as a query engine Integrated Infrastructure for Big Data and Analytics on Hadoop. Vertica SQL on Apache Hadoop offers provides an end-to-end architecture for processing an enterprise-ready method for performing SQL high volumes of structured and unstructured data, for queries on Hadoop data. Using years of experience both real-time use and archival storage. in the big data analytics marketplace and opening Vertica to use the full power of Hadoop, organizations can perform analytics regardless of the data format. Cisco UCS 6300 Series Fabric Vertica SQL on Apache Hadoop handles mission- Interconnects critical analytics projects by merging the best of their Cisco UCS 6300 Series Fabric Interconnects provide analytics platforms with the best that Hadoop data high-bandwidth, low-latency connectivity for servers, analytics can offer. The following principles help to with Cisco UCS Manager providing integrated, deliver on the promise of: unified management for all connected devices. The Cisco UCS 6300 Series Fabric Interconnects are a core • A unified analytics platform merging the economics part of Cisco UCS, providing low-latency, lossless of Hadoop with the power of Vertica 40 Gigabit Ethernet, Fibre Channel over Ethernet • Complete SQL support
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