On Premises
Vertica is the most advanced unified analytics warehouse built from the very first line of code to address the most demanding Big Data analytics initiatives.
Vertica delivers speed without compromise, scale without limits, and the broadest range of consumption and deployment models. The core, unified architecture supports all leading BI and visualization tools and works with your current ETL tools to empower your analytics. Vertica helps you derive more value from your Enterprise Data Warehouse and data lakes and get to market faster with your analytics initiatives.
Fast loading and querying
Ensures extremely high query concurrency, while simultaneously loading new data into the system. Use Flex Tables to query unstructured data in your system.
Advanced in-database analytics
Conduct the analytics computations closer to the data with in-database Machine Learning, and get immediate answers from a massively scalable analytical platform, all based on SQL. And, import models built in other platforms and languages like Spark, Python, and SPSS using the PMML format. Models built in Vertica can also be exported for scoring in other systems such as edge nodes for IoT use cases.
Administration and management tools
Tune and control your queries with minimal administration using Vertica’s Database Designer and Administration Tools. Spend less time identifying performance problems and optimizing a database physical design.
Columnar design and data compression
Leverage columnar data storage for significant gains in performance, I/O, storage footprint, and efficiency.
MPP scale-out architecture
Vertica delivers a simple, yet highly robust and scalable MPP analytical database for the masses with linear scaling and native high availability on industry-standard hardware.
Works in your current ecosystem
With support for all leading BI and visualization tools, open source technologies like Apache Hadoop, Kafka and Spark, you can streamline the transition to Vertica to modernize your analytics ecosystem.
Bringing the benefits of cloud innovation to on-premises environments
Until now, the operational efficiency and flexibility that was born in the cloud was unavailable to organizations who wanted to keep their data on-premises.
The future of infrastructure is multi-cloud and hybrid – a mixture of on-premise and cloud environments – and innovative data management and analytics practices should not be limited to one type of environment.
Vertica in Eon Mode for Pure Storage makes flexible, adaptive analytics possible on-premises.
- Migrating data and analytical workloads often carries unforeseen costs and risks. Vertica in Eon Mode for Pure Storage and MinIO and Hadoop communal storage delivers the benefits of cloud to on-premises data centers.
- Leverage the separation of compute and storage architecture from on-premises data centers and scale compute resources up or down based on demand.
- Isolate workloads for departments or projects without replication using subclusters.
In-Database Machine Learning
With Vertica, there’s no need to maintain two different systems and thus two different storage locations for the same data to do both analytics and machine learning. Vertica offers speed at scale, even when concurrent users are performing analytics. Vertica supports both data scientists and SQL professionals with a single solution. Learn more in this webinar entitled “Introduction to Vertica In-database Machine Learning”.
Which edition is right for you?
To ensure you get the best value for your use case, there are now two editions of Vertica – premium and express. With Premium Edition, there are no limits to features, nodes or data size. The Vertica Express Edition includes a subset of Premium Edition features, but is offered at an even more affordable price. For example, it includes all the basic features such as Workload Management, but does not include more advanced features like Live Aggregate Projections. See the table on the right for details.
| Express | Premium | |
| MPP Architecture, High Availability | ✓ | ✓ |
| Role-Based and Column Security | ✓ | ✓ |
| Standard SQL (ANSI 99) | ✓ | ✓ |
| Flex Tables (metered at 1/10th) | ✓ | ✓ |
| DB Designer, Management Console, Elastic Cluster | ✓ | ✓ |
| ORC & Parquet Readers (to query Hadoop data) | ✓ | ✓ |
| Parquet Export | ✓ | |
| UDx’s written in Java and C++, Voltage UDx (Voltage UDx is pre-built and shipped with Vertica) | ✓ | ✓ |
| UDx’s written in Python and R | ✓ | |
| Workload Analyzer | ✓ | |
| Advanced SQL Functions (Analytical, Pattern Matching, Time Series, Geospatial) | ✓ | |
| ROLAP SQL Functions (Rollup Aggregations, Grouping Sets Aggregations, Cube Aggregations, Pivot) | ✓ | |
| Predictive Analytics Functions (e.g. outlier detection, linear & logistic regression, k-means, naïve bayes, random forest, confusion matrix, etc.) | ✓ | |
| Fault Groups, Key Value interface | ✓ | |
| Live Aggregate Projections, Flattened Tables, Text Search | ✓ |
Modernizing Your Data Warehouse for Cutting-Edge SQL Analytics
Is your aging data warehouse system running out of gas? Download this report and learn how you can easily update your data warehouse to handle more data and complex analytics without spending millions in additional capacity expansion costs.