Rely on an efficient analytical database that uses less hardware and storage than comparable analytics solutions, enabling lower costs and an improved carbon footprint.
Elevate all your analytics—from descriptive to predictive—with a platform that works with SQL, Python, or your preferred visualization tool.
Scale your cloud resources quickly and easily to meet peak workloads while allowing users to run queries 10–50 times faster.
Tap into AI, machine learning (ML), and business intelligence (BI) with a fast, scalable analytics platform.
Employ an analytical database that can use ANSI-Standard SQL, Python, or other languages to satisfy even the most demanding analytics use cases.
Leverage the power of a data lakehouse to analyze all data—wherever it resides and in any popular format—and unlock the necessary speed and scale for better BI and AI.
Optimize data analytics by scaling intelligently and efficiently, using minimal hardware resources to reduce both compute and storage costs.
Utilize cluster-optimized machine learning algorithms, R, and Python to create, train, and test advanced ML models on massive data sets—supported by in-database ML.
Encrypt data in use, in motion, and at rest with end-to-end data protection to secure sensitive data and reduce the risk of a data breach.
Connect to any data integration or visualization tools with hundreds of connectors, seamlessly integrating with your existing architecture.
Speaks SQL, R, Python, Java, C/C++, and other languages so everyone in the organization can access analytics without having to write special queries or consider data structure.
Offers more than 650 built-in analytical functions, including time series, event pattern matching, geospatial, and in-database ML.
Analyzes data wherever it resides—HDFS or Cloud Object Storage—and in all popular formats—ORC, Parquet, JSON, or ROS (native Vertica)—so users can realize insights faster and more efficiently.
Provides end-to-end security with support for industry-standard protocols and partner solutions, such as LDAP, Kerberos, TLS, FIPS 140-2, AWS IAM, and Apache Sentry.
Deploy analytics anywhere leveraging the servers and storage you already have.
Develop a wide range of analytics that inform and predict, using in-database ML to learn and decide on the biggest data sets.
Access data stored in your data lake the same way you would with your data warehouse data, using support for popular lakehouse formats like Parquet and AVRO.
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