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Vertica
Is your aging data warehouse system slowing you down? Are you struggling to derive timely insights from the massive volumes of data entering your organization from old and new sources?
Vertica is an advanced unified analytics warehouse, architected to address the most demanding Big Data Analytics initiatives.
Vertica’s SQL Data Warehouse is trusted by the world’s leading data-driven companies, including Cerner, The Trade Desk, Intuit, Uber, and more to deliver speed, scale, and reliability on mission-critical analytics. Vertica combines the power of a high-performance, massively parallel processing SQL query engine with advanced analytics and machine learning so you can unlock the true potential of your data with no limits and no compromises.
Vertica integrates with popular commercial and open source tools to fit seamlessly into your existing data infrastructure, accelerating analytic insights and machine learning projects so you can transform your data into a competitive advantage.
QuickSpecs
QuickSpecs
QuickSpecs (PDF)
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What's New
- Vertica is now available directly from Hewlett Packard Enterprise.
- Vertica 10 introduces Predictive Model Mark-up Language (PMML) and TensorFlow integration to help organizations operationalize Machine Learning at scale.
Key Features
Analyze All of your Data
Vertica does not require the user to move data or settle for siloed views.
Provides a single platform for data warehouse modernization and data lake exploration.
Leverages all of your data for business intelligence and data science.
Achieve Scale and Performance
Vertica mitigates the fear of growing data volumes and users.
Vertica is architected for blazing fast performance on massive volumes of data.
Get responses to complex queries quickly, while scaling data and users linearly.
Operationalize Machine Learning
Vertica’s in-database machine learning supports the entire predictive analytics process with massively parallel processing and a familiar SQL interface.
Vertica eliminates the most common barriers for enterprise organizations who want to deploy machine learning models in production.
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