Overview

OpenText™ Analytics Database (Vertica) gives organizations access to faster decision-making and operational efficiency with high-performance, real-time analytics and in-database machine learning. Its flexible deployment across hybrid, multi-cloud, and on-premises environments enables better infrastructure-workload alignment to optimize resource use and reduce total cost of ownership. Accelerate adoption, get quick access to business insights, and start driving smarter, faster decisions.

How OpenText Analytics Database can benefit business

Personalize customer experiences

Improve engagement, loyalty, and revenue by using advanced analytics to personalize customer journeys and create targeted, data-driven interactions.

Boost operational efficiency

Streamline operations with data insights to optimize workflows, reduce waste, and anticipate issues like equipment failures—minimizing downtime and costs.

Enhance decision-making

Transform data into actionable insights with advanced analytics, allowing business leaders to make faster, more informed strategic decisions.

Detect fraud and manage risk

Improve fraud detection and risk mitigation before they impact operations or profitability, using machine learning to identify patterns and anomalies.

Accelerate revenue growth

Identify new opportunities, optimize pricing strategies, and improve marketing efforts with data analytics—driving increased revenue and market share.

Reduce time to market

Speed up product development by using analytics to identify trends, streamline processes, and make informed decisions—leading to better products and faster launches.

Why OpenText Analytics Database?

Optimized compute to scale, speed, and save

Enjoy unmatched scalability and lightning-fast performance. Boost your analytics power while lowering total cost of ownership—more power, less spend.

Deploy your way, play your way

Cloud, on-premises, or hybrid? The choice is yours. Seamlessly deploy and maintain control—wherever your data resides—for rockstar analytics power with zero fuss.

Built-in ML, no extra baggage

Get genius-level insights with built-in machine learning. From SQL wizards to Python pros, dive into predictive magic—right out of the box!

Key features

Massively parallel processing (MPP)

Executes analytics across massive datasets with an MPP architecture, delivering high-speed performance and scalability for complex, resource-heavy queries, no matter the data size.

Real-time analytics

Processes and analyzes incoming data in real time, providing ultra-low-latency insights that enable immediate action for time-sensitive applications and dynamic data environments.

Columnar storage

Optimizes query performance and storage efficiency by storing data in columns—improving read speeds for analytical workloads and reducing the overall disk I/O requirements.

Data lakehouse compatibility

Seamlessly analyzes data wherever it’s stored—whether in a data lake, warehouse, or cloud object storage—using popular formats like Parquet, ORC, AVRO, or our native ROS.

Standards-based analytics

Runs analytics using SQL, R, Python, Java, or C/C++, allowing both technical and non-technical users to interact with data and execute queries without special handling.

In-database machine learning

Enables users to build, test, and deploy ML models within the product, processing vast datasets with minimal latency and no data movement for real-time insights and analytics.

Flexible deployment

Deploys analytics on-premises, in the cloud, or in hybrid environments, leveraging your existing infrastructure to tailor solutions based on specific business and technical needs.

In-database analytics

Performs advanced analytics with over 650 built-in functions, including time series, geospatial, and event-pattern matching, enabling deep data insights without external tools.