Vertica Announces Vertica 11, Realizing Vision of Unified Analytics
BOSTON, July 20, 2021 / PRNewswire / – At Vertica Unify 2021, Vertica announced the Vertica 11 analytics platform, which includes major features and enhancements to deliver unified analytics and machine learning across multi-cloud and multi-regional deployments with workflows self-service containers to meet the agility, speed and security demands of the most analytical organizations. With Vertica 11, organizations can unify their data silos and choose from the broadest deployment options with enhanced automation capabilities to sustain their analytics and machine learning for measurable business value.
“Unified Analytics is a vital movement in our industry. But truly unified analytics requires proven and mature security, true deployment choice, end-to-end machine learning in production, and uncompromising analytical performance for organizations to capitalize on this mega trend. ” mentionned Colin Mahony, Senior Vice President and General Manager, Vertica, Micro Focus. “In Vertica 11, we extended Vertica in Eon mode to the Azure cloud, provided support for Docker and Kubernetes containers, extended our market lead in advanced analytics and machine learning, including time series forecasting. , And much more. The list of features goes on and on. – Vertica 11 truly is the unified analytics platform with the fastest performance on an unlimited scale. ”
Vertica 11 includes more machine learning capabilities in the database with the latest version of VerticaPy, an open source Python library for Vertica that supports Python projects on data stored in Vertica. VerticaPy now includes extended machine learning features, connection and data mining capabilities as well as graphics capabilities. Additionally, this release features a new open source Apache Spark connector that supports Spark 3.0 and Scala 2.12 with S3, SSO and parallel read / write support, dramatically improving performance. Additional key features include an XG Boost algorithm, increased PMML integrations, and custom time series algorithms.
“Running database analytics and machine learning will be a real game-changer for Jaguar Racing,” says Phil charles, Technical Director, Jaguar Racing. “With access to all data, over 700 functions in the database and blazingly fast query results, Vertica helps us make urgent decisions to ultimately deliver an edge that leads to more points, podiums and more. wins for Jaguar Racing. “
With Vertica 11, Vertica in Eon mode – Vertica’s cloud-optimized architecture that separates compute from storage for fast elasticity and better cost control – is now in full production on the Microsoft Azure cloud, in addition to AWS and Google Cloud. Vertica is also welcoming Dell EMC ECS as a Certified Object Storage Partner for Eon Mode deployments for private on-premises data centers. Vertica now supports Eon mode database in a Kubernetes StatefulSet, further meeting the commitment to deployment flexibility in multi-cloud and on-premises datacenters.
Vertica 11 highlights and improvements also include:
Widest deployment support
- Eon mode support for Microsoft Azure – Vertica in Eon mode now officially supports Microsoft Azure Block Blob storage, giving organizations complete freedom to choose a proven, cloud-optimized architecture across all three major clouds.
- Support for Docker and Kubernetes containers – The Docker image tested by Vertica is now available on Dockerhub. With this support, organizations now have even more options for cloud native deployments, with container orchestration and Kubernetes. Support for Vertica Kubernetes Operator, StatefulSets, and Helm Charts is included.
- FIPS 140.2 Compliant – Vertica complies with FIPS 140-2, which is used by federal agencies when organizations specify cryptographic security systems for the protection of sensitive or valuable data.
- Improved voltage integration – Improvements to the tight and seamless integration with Voltage SecureData ensure even more secure Format Retention Encryption (FPE) of data, including data masking and format-preserving hash.
- Simplified security configurations – Vertica dramatically simplified security processes to make it easier and more streamlined for restricting and granting user and group privileges
End-to-end machine learning
- Extended time series support – Time series forecasting is significantly expanded to include support for autoregression, moving average, stationarity tests, and automatic generation of correlation plots in the database using SQL and VerticaPy.
- Spark 2.0 Connector – Vertica contributed to an improved connection with Spark which now supports Spark 3.0 and 3.1 with more efficient two-way data flows, projections and filters, SQL pushback and support for enterprise single sign-on , including Kerberos.
- VerticaPy – VerticaPy is a new open source Python library that exposes Pandas and Scikit-like functionality for conducting data science projects on data stored in Vertica, combining the scalability of Vertica with the flexibility of Python.
- AutoML – VerticaPy Delphi, our most advanced auto-ML capability yet, can automatically prepare data, train and evaluate multiple algorithms, and display a graph accurately and efficiently in minutes, using comprehensive Vertica data sets to Greatly shorten development time for Machine Learning and AI Projects.
- XGBoost – XGBoost is the latest algorithm added to the long list of database algorithms supported by Vertica. The Auto-Retrain meta function ensures that models consistently produce accurate predictions.
- Extensive Deep Learning and PMML Support – Vertica now supports importing the latest version of TensorFlow, version 2.5, deep learning and custom models. Importing generalized linear models from PMML is also supported.
Increased analytical performance and much more
- Stored procedures – Vertica 11 introduces stored procedures to automate the information lifecycle from ELT, through data preparation, to ML pipeline. Vertica has a rich set of features at every stage of the lifecycle and usage pipeline. Stored procedures will allow users to automate their execution and facilitate the collection of metadata for audit and forensics.
- Extended support for complex data types – Analysis of complex data types such as maps, tables and structures is now extended with the improved ability to export data in these forms directly to ORC as well as Parquet, and full ability to query files with complex types in place, without modification or import.
- Management Console (MC) enhancements – The MC features several enhancements, including quick launch templates to get you working faster, streamlined workflows to help you work more efficiently, and customizable alerts and monitoring metrics to keep your job running smoothly. your Vertica cluster.
- Query Optimization Improvements – Increasing the speed of any query containing a WITH clause will show the marked difference in the ongoing improvements to the query optimization engine.
For more information on Vertica 11, please visit www.vertica.com.
To learn more about Vertica on Twitter, please follow @VerticaUnified and join Vertica on LinkedIn and Facebook.
The primary analytical platform of the Micro Focus software portfolio, Vertica is the unified, massively scalable architecture-based analytics platform with the broadest set of analytical capabilities and end-to-end machine learning in the industry. database. Vertica enables many customers – from Philips to The Trade Desk to MassMutual to many others – to easily apply these powerful functions to the largest and most demanding analytical workloads, providing businesses and their customers with insight. predictive business faster than any data analytics platform on the market. Vertica provides its unified analytics platform across all major public clouds and on-premises data centers and integrates the data into cloud object storage.
Contact: Lauren Warble, [email protected]