HPE Big Data Platform Software Portfolio

HPE Vertica Speed without compromise, scale without limits, and consumption models on premise, in the cloud, and on Hadoop.

HPE Vertica analytics platform Fast Boost performance by 500% or more Scalable Handles huge workloads at high speeds Standard No need to learn new languages or add complexity Costs Significantly lower cost over legacy platforms

HPE Vertica portfolio The broadest range of deployment and consumption models HPE Vertica in the Cloud Get up and running quickly in the cloud Flexible, enterprise-class cloud deployment options HPE Vertica Enterprise Columnar storage and advanced compression Maximum performance and scalability Flex Tables for schema-on-read Vertica unified platform Cloud On-Premise On Hadoop HPE Vertica Portfolio Messaging: HP Vertica is an industry-leading, purpose built analytics database portfolio built from the first line of code to address the 21st century generation of data analytics requirements. HP Vertica was built to deliver speed without compromise, scale without limits, at a dramatically reduced cost due to MPP processing and data compression. HP Vertica offers consumption model options including on-premise (Vertica Enterprise (Premium & Express Editions), in the cloud (Vertica on Amazon – via our AMI {Amazon Machine Image} Edition), on demand (Vertica OnDemand) and for data stored in Hadoop (Vertica SQL on Hadoop) for native Hadoop node analytics. Only Vertica offers this extensive spectrum of consumption modes all featuring Vertica’s core capabilities to deliver best-in-class performance and scalability Vertica is designed to work seamlessly in a complex Big Data Ecosystem, offering visualization choices, data integration and ingestion options, and connectors for all forms and sources of data. HP Vertica offers enterprise grade security and stability with the highest levels of proven quality. Portability – Since All Vertica consumption models are based on the same Vertica core technology in most cases it is a simple task to shift from one consumption mode to another. For example if an enterprise wanted to take their Vertica Enterprise in house based deployment to the Amazon Cloud this would be very straightforward utilizing our AMI version offering. HPE Vertica for SQL on Hadoop Native support for ORC, more Support for industry-leading distributions No helper node or single point of failure

Vertica On-Premise Vertica On-Premise HPE Vertica in the Cloud Get up and running quickly in the cloud Flexible, enterprise-class cloud deployment options HPE Vertica Enterprise Columnar storage and advanced compression Maximum performance and scalability Flex Tables for schema-on-read Vertica On-Premise Install and manage in-house Leverage in-house hardware Reference architectures available for optimal performance HPE Vertica for SQL on Hadoop Native support for ORC, more Support for industry-leading distributions No helper node or single point of failure

Vertica On-Premise Built for speed HPE Vertica for insanely high query performance Use to take Now takes 1 hour 3.6 Seconds 8 hours (overnight) Under 30 seconds Slides that follow describe how we achieve such huge performance increases

Vertica Enterprise Edition On-premise Big Data analytics Columnar store Aggressive data compression Projections and optimizations No hassle optimizations MPP architecture HA architecture HPE reference architectures available The ultimate in scalability ANSI SQL compliant Java, Python, R APIs ACID compliance Large ecosystem of partners and connectors Compatible with your analytical applications Management console Database designer Easy to manage

Increased performance Reduced footprint & cost Vertica On-Premise Increased performance 50x-1,000x faster than legacy data warehouse Massive scalability Infinitely and easily scale your solution Reduced footprint & cost 10x-30x more data per server Simple per Terabyte pricing HP Confidential 8 5 May 2018

Foundations of Vertica Columnar storage Compression MPP scale-out Distributed query Projections Speeds query time by reading only necessary data Lowers costly I/O to boost overall performance Provides high scalability on clusters with no name node or other single point of failure Any node can initiate the queries and use other nodes for work. No single point of failure Combine high availability with special optimizations for query performance Memory CPU Disk A B D C E

Designed for advanced workload management Polyglot persistence Install HP Vertica directly on your Hadoop, on-premises or cloud infrastructure Control mixed workloads Leverage Typical queries Sample data/schemas Historical statistics and logs Optimize Query performance Data loading Storage footprint Benefit Faster queries Lower hardware costs Shortened design time Lower costs to maintain and optimize Database designer Analytical applications R Java Python SQL HPE Vertica Core engine Store: ROS Ingest: AVRO, JSON, etc. Query: ORC & Parquet Represents increasingly divergent market demands — ongoing traditional, logical data warehousing, operational data warehousing and context-independent data management for analytics (for definitions see "Critical Capabilities for Data Warehouse Database Management Systems" ). The largest and most traditional portion of the analytics and data warehouse market is still dominated by the demand to support relational analytical queries over normalized and dimensional models (including simple trend lines through complex dimensional models). Data management for analytics' solutions are increasingly expected to include repositories, semantic data access (such as federation/virtualization) and distributed processing in combination — referred to in the market as LDWs. All traditional demands of the data warehouse remain. Operational data warehouse use cases also exhibit traditional requirements plus loading streaming data, real- time data loading and real-time analytics support. Users expect solutions to become self-tuning, to reduce staffing required to optimize the data warehouse, especially as mixed workloads increase. Context-independent warehouses (CIWs) do not necessarily support mixed workloads (but can), nor do they require the same level of mission-critical support. CIWs serve more in the role of data discovery support or "sandboxes." Management console

Vertica Works seamlessly with your current infrastructure Data transformation and ETL partners Data visualization and BI partners Slides that follow describe how we achieve such huge performance increases

HPE Vertica Community and Enterprise edition details Analytics at Scale Community Enterprise MPP architecture ✓ High availability Role-based security Standard SQL (ANSI 99) Flex tables Workload analyzer, DB designer, Mgmt console License available for more than 1TB License available for more than 3 nodes Free to use Simple (per TB) pricing *Advanced analytics functions (SQL Windowing Functions, approximate count distinct and Advanced SQL functions such as Time Series, Conditional Change Events, Sessionization Event Series Joins, and Gap Filling Interpolation ) HPE Vertica Express and Premium Edition Details HPE Vertica Express Edition includes the core features of the industry’s leading MPP analytics database platform, including high availability, roles-based security, user-defined extensions, standard ANSI SQL, Flex Tables for schema on read, database management and designer capabilities, and more. All at just $10K per TB. HPE Vertica Premium Edition includes all of the features of HPE Vertica Express Edition with fault groups, the KV interface, added analytical functions for geospatial and sentiment analysis, R extensions, enhanced security, and Live Aggregate & Pre-Join Projections. All at $25K per TB. On-Premise

Vertica in the Cloud Vertica on AMI HPE Vertica in the Cloud Get up and running quickly in the cloud Flexible, enterprise-class cloud deployment options HPE Vertica Enterprise Columnar storage and advanced compression Maximum performance and scalability Flex Tables for schema-on-read HPE Vertica Portfolio Messaging: HP Vertica is an industry-leading, purpose built analytics database portfolio built from the first line of code to address the 21st century generation of data analytics requirements. HP Vertica was built to deliver speed without compromise, scale without limits, at a dramatically reduced cost due to MPP processing and data compression. HP Vertica offers consumption model options including on-premise (Vertica Enterprise (Premium & Express Editions), in the cloud (Vertica on Amazon – via our AMI {Amazon Machine Image} Edition), on demand (Vertica OnDemand) and for data stored in Hadoop (Vertica SQL on Hadoop) for native Hadoop node analytics. Only Vertica offers this extensive spectrum of consumption modes all featuring Vertica’s core capabilities to deliver best-in-class performance and scalability Vertica is designed to work seamlessly in a complex Big Data Ecosystem, offering visualization choices, data integration and ingestion options, and connectors for all forms and sources of data. HP Vertica offers enterprise grade security and stability with the highest levels of proven quality. Portability – Since All Vertica consumption models are based on the same Vertica core technology in most cases it is a simple task to shift from one consumption mode to another. For example if an enterprise wanted to take their Vertica Enterprise in house based deployment to the Amazon Cloud this would be very straightforward utilizing our AMI version offering. Vertica on AMI HPE Vertica for SQL on Hadoop Native support for ORC, more Support for industry-leading distributions No helper node or single point of failure

HPE Vertica for Amazon Consume and deploy via the cloud HPE Vertica Amazon Machine Image (AMI) What? An AMI for installing your Vertica license on dedicated cloud instance on Amazon Web Services cloud platform. http://amzn.to/1OLVe4C Why? No need to worry about managing the infrastructure, but still control your own instance without the burden of physical environment. HP Vertica for Amazon: Consume and Deploy via the Cloud Customers Can Choose HP Vertica AMI HP Vertica AMI (https://aws.amazon.com/marketplace/pp/B010ETKZKG/ref=srh_res_product_title?ie=UTF8&sr=0-2&qid=1442524965705) For data architects, DBAs, and traditional Vertica users that prefer a “hands-on” approach to selecting and configuring hardware and tuning queries for optimal performance in a prescribed way on AWS, the HP Vertica AMI simplifies deployment, while affording organizations with the same control as if the cluster was managed locally on-premise.   Simplification and Rapid Deployment: Customers can install Vertica on Amazon Elastic Compute Cloud (Amazon EC2) instances and enjoy our more advanced and more complete analytical capabilities. New Ways to Achieve Enterprise-Class Analytics: HPE Vertica Editions offer organizations a path to scale up and down based on the analytic demands of their enterprise and ensure maximum uptime to meet SLAs with HP Vertica’s trusted architecture. Customers can benefit by having the same analytical engine, available both on premise and in the cloud. Kiva, a global non-profit organization, uses the for Big Data analytics as it leverages the internet and a worldwide network of microfinance institutions to help individuals lend as little as $25 to create opportunity around the world. RetailMeNot, Inc. operates the world's largest marketplace for digital offers. The company enables consumers across the globe to find hundreds of thousands of digital offers for their favorite retailers and brands. Three years ago, RetailMeNot was still a small startup with a 600GB database, a database management system that wouldn't handle the load, and exponential data growth around the corner. HP Vertica has scaled to support its rapid growth in the last three years to 44TB, and provides the company with a wealth of business analytics and great performance. Utilizing HP Vertica, RetailMeNot can now test new products, a critical element for providing competitive web service, in near real-time and effectively analyze massive amounts of customer data for new product initiatives and better customer service and offerings.

HPE Vertica Enterprise by program and edition On-premise and AMI hosted offerings to address varying needs COMMUNITY Free Evaluators Up to 1 TB capacity Up to 3 nodes Community-Based Support No Time Constraints START-UP ESSENTIALS Free Start-ups <10 employees One-Year Term Up to 3 TB capacity Community-Based Support Online Training EXPRESS Priced per TB Analytics at Scale MPP Architecture High Availability User and System Management Flex Tables PREMIUM No Limits, Compromises Extends Express Capabilities Large-Scale Deployments Advanced Use Cases Granular Security Priced per TB HPE Vertica Enterprise is available in the following on-premise offerings to address the varying needs – from start-up organizations to the most demanding, data-driven enterprises: - HPE Vertica Community Edition – Available for free for up to 1 TB of capacity across three nodes with community-based support and no time constraints. - HPE Vertica Start-Up Essentials Program – Also available for free for one year for start-ups with fewer than 10 employees. These start- ups can store up to 3 TB of data with community-based support and online training. After the initial year, attractive commercial pricing is available. - HPE Vertica Express Edition – For organizations that need to run big data analytics at scale, the Express Edition is available at an attractive $15K per TB. Licensing is available as perpetual or term with maintenance and phone support. - HPE Vertica Premium Edition – For the most demanding, data-driven enterprises, HPE Vertica Premium Edition offers the full features and functionality of the industry’s leading MPP analytics database platform at just $25K per TB. Licensing is also available as perpetual or term with maintenance and phone support.

HPE Vertica Express and Premium edition details Analytics at Scale Express Premium MPP architecture ✓ High availability Role-based security User function creation (UDx) Standard SQL (ANSI 99) Flex tables Workload analyzer, DB designer, Management console Elastic cluster Advanced SQL analytics (time series, SQL windowing, gap flling, more)* Fault groups Key value interface Sentiment, geospatial, R extensions Column security Live aggregate & pre-join projections *Advanced analytics functions (SQL Windowing Functions, approximate count distinct and Advanced SQL functions such as Time Series, Conditional Change Events, Sessionization Event Series Joins, and Gap Filling Interpolation ) HPE Vertica Express and Premium Edition Details HPE Vertica Express Edition includes the core features of the industry’s leading MPP analytics database platform, including high availability, roles-based security, user-defined extensions, standard ANSI SQL, Flex Tables for schema on read, database management and designer capabilities, and more. All at just $10K per TB. HPE Vertica Premium Edition includes all of the features of HPE Vertica Express Edition with fault groups, the KV interface, added analytical functions for geospatial and sentiment analysis, R extensions, enhanced security, and Live Aggregate & Pre-Join Projections. All at $25K per TB. No Limits No Compromises

Vertica On Hadoop HPE Vertica for SQL on Hadoop HPE Vertica in the Cloud Get up and running quickly in the cloud Flexible, enterprise-class cloud deployment options HPE Vertica Enterprise Columnar storage and advanced compression Maximum performance and scalability Flex Tables for schema-on-read HPE Vertica for SQL on Hadoop HPE Vertica Portfolio Messaging: HP Vertica is an industry-leading, purpose built analytics database portfolio built from the first line of code to address the 21st century generation of data analytics requirements. HP Vertica was built to deliver speed without compromise, scale without limits, at a dramatically reduced cost due to MPP processing and data compression. HP Vertica offers consumption model options including on-premise (Vertica Enterprise (Premium & Express Editions), in the cloud (Vertica on Amazon – via our AMI {Amazon Machine Image} Edition), on demand (Vertica OnDemand) and for data stored in Hadoop (Vertica SQL on Hadoop) for native Hadoop node analytics. Only Vertica offers this extensive spectrum of consumption modes all featuring Vertica’s core capabilities to deliver best-in-class performance and scalability Vertica is designed to work seamlessly in a complex Big Data Ecosystem, offering visualization choices, data integration and ingestion options, and connectors for all forms and sources of data. HP Vertica offers enterprise grade security and stability with the highest levels of proven quality. Portability – Since All Vertica consumption models are based on the same Vertica core technology in most cases it is a simple task to shift from one consumption mode to another. For example if an enterprise wanted to take their Vertica Enterprise in house based deployment to the Amazon Cloud this would be very straightforward utilizing our AMI version offering. HPE Vertica for SQL on Hadoop Native support for ORC, more Support for industry-leading distributions No helper node or single point of failure

HPE Vertica for SQL on Hadoop users Analysts no longer need to care where the data is located or how it is stored. They can use favorite BI/data visualization tools. HPE Vertica ANSI SQL Fastest HPE Veritica for SQL on Hadoop Users Analysts are most interested in using their preferred BI/data visualization tools to provide analytical insight to the organization in the form of dashboards and reports. They are less concerned with where the data stored, provided that they can actually query the data and visualize the results. DBAs are under duress in handling the various workloads and requests from the organization. Using Hadoop for less-demanding, less- intensive analytical requests to tier off colder data and tapping into the rich, high-performance analytics on data stored in the ROS format helps them to address the full and varying needs of internal and external users. Data Engineers can ingest all emerging forms of data, including AVRO and JSON, from sensor data and log files for increasingly popular analytical use cases. For top performance, these data engineers can store data in the highly optimized Vertica ROS format. If their organization is looking to derive value from the existing data stored in Hadoop data lakes – such as ORC and Parquet – HPE Vertica for SQL on Hadoop can fit that need, too. DBAs now have a single way to access data whether it is in Hadoop or Vertica and implements complete Information Life Cycle Management. HP Vertica Optimized Storage Fast Hadoop Storage Data engineers can now use SQL in addition to MapReduce, Hive, etc. to explore and analyze the data.

HPE Vertica for SQL on Hadoop features and benefits Engine is flexible enough to perform analytics on data no matter where it lives - Hadoop, native Vertica or in the cloud. Unified analytics engine Get full ANSI SQL 99 compliance that is able to execute 100% of the TPC-DS benchmarks without modification. Complete SQL support Vertica can quickly and efficiently query ORC files for fast analytics without moving the data. Other formats like Parquet and AVRO are also supported. Fast ORC file reader Convenient, graphical application supports Ambari to check the health of both the Vertica and Hadoop clusters and their queries. Supports storage labels for resource allocation in YARN. YARN and Ambari Platform supports Kerberos to provide security and encryption with a single authentication to both Vertica and Hadoop services Secure with Kerberos Unlike other SQL on Hadoop solutions, Vertica installs direct on your Hadoop nodes with no need for a helper node. No single point of failure HPE is focused on the deep integration of our SQL engine with any distribution of Hadoop. Hewlett Packard Enterprise has partnered with Hortonworks, Cloudera, and MapR and others to bring you a flexible analytics platform that performs seamlessly across major distributions. Platform agnostic HPE Vertica for SQL on Hadoop Features and Benefits HPE Vertica for SQL on Hadoop offers you the most enterprise-ready way to perform SQL queries on your Hadoop data. We’ve leveraged our years of experience in the big data analytics market and further opened up our platform to tap into the full power of Hadoop. By offering a rich, fast, and enterprise-ready implementation of SQL on Hadoop, you can perform analytics regardless of the format of data or Hadoop distribution. HPE Vertica for SQL on Hadoop handles your mission-critical analytics projects by merging the best of our analytics platform with the best that Hadoop can offer. In addition to the key features and benefits listed in the slide above, the principles below drive us to deliver on these promises: Platform Agnostic. HP is focused on the deep integration of our SQL engine with any distribution of Hadoop. HP has partnered with Hortonworks, Cloudera, and MapR and Apache to bring you a flexible analytics platform that performs seamlessly across all of your Hadoop distributions. Enterprise Ready. HP has experience with petabyte scale deployments and world-class enterprise support and services organization. With HPE Vertica for SQL on Hadoop, businesses can minimize switching costs and learning curves for users with the familiar ANSI SQL syntax. Analysts can continue to use familiar BI/analytics tools that assume and auto-generate ANSI SQL code to interact with any Hadoop distribution. HPE Vertica for SQL on Hadoop ingests all new incoming and emerging data formats, such as AVRO, JSON, and more. Data is persisted and stored in the highly optimized ROS format for top performance. For organizations that want to derive more value from their existing data lakes, they can query ORC & Parquet data in place without copying or moving the data.

VSQLH is reliable and performant Up to 2x slower Comparable Up to 7x faster 43 queries more! In this industry-standard benchmark: 43/99 queries will not run in other solutions that work unchanged in VSQLOH Concurrency is better supported Security with Kerberos Some queries run up to 7X faster on HPE SQL on Hadoop

New ORCFile reader Before After Hcat Connector ORC Reader Open Source Project jointly developed by Vertica and Hortonworks Engineers Query close to where data resides Column Pruning, Predicate Pushdown Hadoop data nodes Hadoop data nodes VSQLH SP1 VSQLH SP2 Before After The ORCReader project as I mentioned before is Open Source on GitHub. Interestingly we have had contributors from Microsoft, but the majority of the code is from HWX and Vertica. The team in Pittsburg is happy to announce this project being pushed upstream into the main Apache Hadoop project. The ORCReader is a NEW way to directly access ORCFile formatted data and replaces the initial access method used via Hcat Connector. Instead of using SerDes, the ORCReader uses External Table mechanism to access ORC data. Hcat Connector SerDes WebHCat ORC Reader External table WebHDFS HDFS ORCFiles HDFS ORCFiles

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