1. HPE Big Data Platform
Software Portfolio

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

3. 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

4. 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

5. 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

6. 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

7. 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

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

14. 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.
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 (
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.

15. 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.

16. 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

17. 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

18. 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.

19. 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.

20. 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

21. 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

22. Thank you
Thank you.