Data Sheet Analytics and Big Data Vertica Overview The Vertica Analytics Platform delivers speed, scalability, and built-in analytics that today’s most analytically intensive workloads demand, whether in the public clouds, on-premises, on Hadoop, or any hybrid combination. Key Benefits Key Features ■ Flexibility and scalability to easily ramp up when workloads increase. Step Up to the Fastest, Most Flexible At the core of the Vertica Advanced Analytics Platform is a column-oriented, relational data- Big Data Analytics Platform ■ Better load throughput and concurrency base built specifically to handle today’s analytic What should you look for in a data analyt- with querying. workloads. The Vertica Analytics Platform pro- ics warehouse to address today and tomor- ■ In-database machine learning addressing vides you with: row’s data challenges? Consider the following every step in the ML process—algorithms, Vertica capabilities: ■ Complete and advanced SQL-based R support, Python extensibility, and more. analytical functions to provide powerful ■ Analyze huge data volumes in a unified ■ Analyze data in place and in any format, SQL analytics. manner: You can analyze data at unlimited including complex data types like Maps scale, and finally combine data siloes that ■ A clustered approach to storing big data, and Arrays, Structs in Parquet on S3, are growing exponentially. offering superior query and analytic HDFS, open SQL-based analytics, and new performance. use cases. ■ Save on both storage and computational charges: While cloud-based data storage ■ Better compression, requiring less ■ Vertica in Eon Mode provisions dynamic is low cost, analyzing that data can lead to hardware and storage than comparable workloads as needed, separates storage prohibitively expensive compute charges. data analytics solutions. and compute, and enables workload. Vertica in Eon Mode manages dynamic workloads, so you can spin up storage and Built-in Functions Analyze External Tables in the Right Place compute resources as you need them, Geospatial Machine Learning Event Series Text Analytics Parquet HDFS and spin then down afterward to eliminate Time Series Pattern Matching Amazon S3 Apache ORC unnecessary costs. Real-Time Regression Statistics ■ Meet business expectations: Users don’t want to wait for results. Vertica provides the Data Visualization On-Premises Deployment Options scalability to meet service level agreements Logi Analytics ODBC Openstack Commodity Hardware (SLAs) and business needs with the best Looker JDBC MINIO Pure Storage Power BI OLEDB Hadoop TCO and fastest ROI, including the ability Qlik to dedicate compute resources to individual Tableau Cloud Deployment Options use cases without replicating the data. User Defined Functions Microsoft Azure ■ Embrace popular tools: Vertica provides R Python Amazon Web Services robust and powerful SQL and is certified Java SQL Google Cloud Platform C/C++ to work with all of your tools—not just those from your primary vendor or limited Security Integrations User Defined Loads to a single infrastructure. Use the extract, LDAP FIPS Data Transformation―(Spark) transform, load (ETL) tools or SQL-based Kerberos Voltage Messaging―(Kafka) visualizations of your choosing. ETL―(Attunity, Informatica) Figure 1. Vertica’s open architecture and rich ecosystem Data Sheet Vertica Overview isolation to serve multiple departments • Statistical Summary • Outlier Detection • Support Vector • Model-level stats • In-Database Machines Scoring without duplicating the data. Vertica in • Time Series • Normalization • ROC Tables • Random Forests • Speed Enterprise Mode is ideal for stable • Machine Learning • Sessionize • Imbalanced Data • Error Rate Speed Processing • Logistic Regression • Scale workloads and regular queries. • Pattern Matching • Lift Table • ANSI SQL • Sampling • Linear Regression • Security • Date/Time Algebra • Confusion Matrix • Scalability • Missing Value • Ridge Regression ■ Runs in the clouds, including Google Cloud •Window/Partition • R-Squared Imputation • Massively Parallel • Naive Bayes • Data Type Handling • MSE Platform (GCP), Azure, AWS, VMware clouds; • and more ... Processing • Cross Validation and runs on-premises with commodity • Sequences • Deploy Anywhere • and more ... hardware and support for a range of object •and more ... stores, such as Apache Hadoop HDFS for communal storage, MinIO, and on Business Data Analysis & Data Preparation Modeling Evaluation Deployment Understanding Understanding Pure Storage FlashBlade S3. SQL SQL SQL SQL Product Overview Figure 2. Vertica built-in machine learning process flow Vertica Analytics Platform provides blazingly fast speed (queries run 10–50X faster), exabyte scale (store 10–30X more data per server), and Operationalize Machine Learning— data compression, so it delivers extremely broad ecosystem integration (use any busi- at Scale fast results, reducing query times from hours - ness intelligence tools, ETL tools, storage, Not long ago, data science was limited by the to minutes, or minutes to seconds—some thing outdated row-store technologies cannot etc.) at a much lower cost than traditional data inability to base models on full data volumes, achieve. warehouses or cloud-only data warehouses. which led to inaccurate predictions. To make matters worse, the majority of machine learn- Vertica offers advanced SQL-based analyt- ing initiatives never make their way into produc- The Power to Handle Today’s ics—from graph analysis, to triangle counting, tion at all, so only portions of the organizations Massive Data Volumes to Monte Carlo simulations, to time series and benefit from the work from data scientists. Modern businesses must manage more data geospatial, and more. All this can be applied to sources than ever before—no longer just CRM your “hot” data loaded directly into Vertica for With Vertica, you can finally operationalize ma - and ERP, systems, but also IoT sensors, social the most demanding use cases. media data, Web logs and data streams, gas chine learning, so that you can understand— and electrical grids, and mobile networks, just and act on—what that data is telling you, with You also get choices. Vertica is the only ad- to name a few. Organizations that are truly the speed and scalability to make a difference. vanced analytics platform that can analyze data-driven must manage this explosive data Vertica’s in-database machine learning sup- data in HDFS, in S3 Object Storage, and within growth, and discover the patterns and trends ports the entire predictive analytics process the Vertica data warehouse itself, including that can lead to new business opportunities, as with massively parallel processing and a fa- the ability to join these disparate data sets well as repeat business from their customers. miliar SQL interface, allowing data scientists into unified analytics. Perhaps most impor- and analysts to build their models using their tant, Vertica offers the broadest choice of The Vertica Analytics Platform answers these preferred tools and languages to embrace the deployment modes—Vertica in Eon Mode for needs. It handles data at exabyte scale, and power of big data and accelerate business dynamic workloads that benefit from a separa- enables your organization to unify data siloes outcomes with no limits and no compromises. tion of compute and storage architecture, and across multiple cloud and hybrid (cloud and on- More details below. Vertica in Enterprise Mode for more predict- premises) environments. Not only can Vertica able workloads on servers with tightly coupled manage massive data volumes, it keeps you The Technology Big Data Demands storage—so you can choose the architecture from getting locked into a single cloud vendor. Vertica is built from the ground up to tackle the that works for you today. Use the tools of your choice, and take full ad- challenges of big data analytics. Its massively vantage of the underlying infrastructure you parallel processing system addresses the Unifying Today’s Big Data Siloes already have in place, with portability across most demanding analytics use cases in the Vertica ensures that all the time, money, and multi-cloud, on-prem, and Hadoop data lakes. industry. Its columnar store offers aggressive effort you’ve put into storing your data turns 2 into business value. It provides a unified analyt- imbalanced data processing, missing value ics platform that can analyze data in place— imputation and more. HDFS or Cloud Object Storage—and in all ■ Create, train, and test advanced machine popular formats—ORC, Parquet, JSON, or ROS learning models on massive data sets. (native Vertica). ■ Evaluate model-level statistics including ROC tables and confusion matrices. Along with eliminating data center mainte- ■ Revert back to previous model iterations Protection of data Protection that scales nance, public clouds have provided the archi- everywhere it goes with big data using model management and version tectural advantage of separating data compute SecureData Cloud provides SecureData delivers and storage, and provisioning on-demand. But control features. security in the cloud across protection that scales with Hybrid IT systems. NiFi the growth of nodes, data high compute charges from any given cloud ■ Massively Parallel Processing (MPP) integration enables IoT volumes and data types vendor can quickly sink your big data budget. architecture allows you to build and deploy protection at the edge Vertica solves this problem when deployed models at petabyte-scale with extreme in Eon