Vertica Analytics Platform
Microsoft Azure SQL Database

Integrate Vertica Analytics Platform with Microsoft Azure SQL Database

About Vertica Analytics Platform

Vertica Analytics Platform is a data warehouse management system optimized for large-scale, rapidly-growing datasets. By using a column-oriented architecture (instead of row-oriented), Vertica can offer high-speed query performance for your business intelligence, machine learning, and other query-intensive systems. Vertica is compatible with a variety of cloud data warehouse servers such as Google Cloud Platform, Amazon Elastic Compute Cloud, Microsoft Azure, and on-premises. The platform also offers its “Eon Mode,” which achieves optimum performance by separating computational processes from storage processes. Eon Mode is available when hosting the platform on AWS or when using Pure Storage Flashblade on-premises. Vertica is an open-source product that is free to use up to certain data limitations.

About Microsoft Azure SQL Database

Microsoft Azure is a public cloud computing service designed for building, testing, launching, and managing applications and services via Microsoft-managed data centers. Through its platform-as-a-service (PaaS), software-as-a-service (SaaS), and infrastructure-as-a-service (Iaas) offerings, Microsoft Azure integrates with a wide range of programming languages and tools. In addition to working with Microsoft’s proprietary software and systems, Azure is compatible with third-party solutions, including Linux. As an extremely popular cloud services platform, many businesses and enterprises have used Microsoft Azure to migrate their computer systems to the cloud and eliminate the costs and staff requirements needed to maintain physical onsite servers.

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Vertica Analytics Platform's End Points

Vertica Massively Parallel Processing (MPP)

Through its MPP architecture, Vertica distributes requests across different nodes. This brings the benefit of virtually unlimited linear scalability.

Vertica Column-Oriented Storage

Veritica's column-oriented storage architecture provides faster query performance when managing access to sequential records. This advantage also has the adverse effect of slowing down normal transactional queries like updates, deletes, and single record retrieval.

Vertica Workload Management Automation

With its workload management features, Vertica allows you to automate server recovery, data replication, storage optimization, and query performance tuning.

Vertica Machine Learning Capabilities

Vertica includes a number of machine learning features in-database. These include 'categorization, fitting, and prediction,' which bypasses down-sampling and data movement for faster processing speed. There are also algorithms for logistic regression, linear regression, Naive Bayes classification, k-means clustering, vector machine regression/classification, random forest decision trees, and more.

Vertica In-Built Analytics Features

Through its SQL-based interface, Vertica provides developers with a number of in-built data analytics features such as event-based windowing/sessionization, time-series gap filling, event series joins, pattern matching, geospatial analysis, and statistical computation.

Vertica SQL-Based Interface

Vertica's SQL based interface makes the platform easy to use for the widest range of developers.

Vertica Shared-Nothing Architecture

Vertica's shared-nothing architecture is a strategy that lowers system contention among shared resources. This offers the benefit of slowly lowering system performance when there is a hardware failure.

Vertica High Compression Features

Vertica batches updates to the main store. It also saves columns of homogenous data types in the same place. This helps Vertica achieve high compression for greater processing speeds.

Vertica Kafka and Spark Integrations

Vertica features native integrations for a variety of large-volume data tools. For example, Vertica includes a native integration for Apache Spark, which is a general-purpose distributed data processing engine. It also includes an integration for Apache Kafka, which is a messaging system for large-volume stream processing, metrics collection/monitoring, website activity tracking, log aggregation, data ingestion, and real-time analytics.

Vertica Cloud Platform Compatibility

Vertica runs on a variety of cloud-based platforms including Google Cloud Platform, Microsoft Azure, Amazon Elastic Compute Cloud, and on-premises. It can also run natively using Hadoop Nodes.

Vertica Programming Interface Compatibility

Vertica is compatible with the most popular programming interfaces such as OLEDB, ADO.NET, ODBC, and JDBC.

Vertica Third-Party Tool Compatibility

A large number of data visualization, business intelligence, and ETL (extract, transform, load) tools offer integrations for Vertica Analytics Platform. For example, Xplenty's ETL-as-a-service tool offers a native integration to connect with Vertica.

Microsoft Azure SQL Database's End Points

Microsoft Azure Virtual Machines

As one of its IaaS features, Microsoft Azure allows users to deploy virtual machines developed in Windows or Linux.

Microsoft Azure App Services

As one of its PaaS features, Azure App Services allows you to publish and manage websites and web applications.

Microsoft Azure WebApps

WebApps is Microsoft Azure's high-density web hosting service, which allows you to build web applications more efficiently with PHP, Node.Js, or Python, then deploy them on the Azure Cloud.

Microsoft Azure WebJobs

WebJobs gives you the ability to launch applications in the Microsoft App Services space and host them in the cloud.

Microsoft Azure Mobile Engagement Services

Microsoft Azure's mobile engagement service provides real-time tracking, data analytics, and deep insights to better understand user engagement and behavior for your mobile applications.

Microsoft Azure HockeyApp

Microsoft Azure's HockeyApp is a productivity-enhancing driver that helps you design, build, beta test, and distribute mobile apps more efficiently.

Microsoft Azure REST and SDK APIs

Azure's REST and SDK APIs allow you to store and access your application data on Azure's cloud platform.

Microsoft Azure Table Services

Azure Table Services facilitates the storage of data in structured text form so you can access it via a partition and primary key.

Microsoft Azure Blob Service

Blob Service empowers you to store unstructured text information and binary data as 'Blobs' accessible through HTTPS.

Microsoft Azure Queue Service

Queue Service streamlines asynchronous communication across multiple programs.

Microsoft Azure File Service

Azure File Service facilitates cloud data storage via REST API and the SMB Protocol.

Microsoft Azure Search Functionality

Azure's data search functionality supports more efficient data searching with REST and SDK APIs.

Microsoft Azure SQL Data Warehouse

Azure's SQL data warehouse is managed by Microsoft within the Azure Cloud Facility. It offers high-performance querying and enhanced data security.

Microsoft Azure Messaging Service

Azure Service Bus is a messaging service that facilitates communication between the Azure Cloud and applications operating on-site and off-site to build more reliable and scalable applications. The Azure Service Bus supports communication via Event Hubs, Queues, Topics, and Relays.

Microsoft Azure Automation Features

Azure Automation allows users to automate frequently-repeated tasks that they perform in their cloud and enterprise environments to save time and prevent human errors. Automation improves the reliability of common administrative tasks. Azure automation allows you to schedule tasks with runbooks or use Desired State Configuration for the automation of configuration management tasks.

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