Securely integrate Vertica Analytics Platform with GoodData
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.
According to the platform’s marketing literature, GoodData’s powers ‘50% of Fortune 500 companies, over 80,000 businesses, and millions of concurrent users.’ With its motto, ‘analytics for everyone,’ the solution offers an easy-to-use, drag-and-drop analytics interface so anyone across your organization — regardless of their tech knowledge — can set up dashboards and explore business insights to collaborate with team members and make better decisions. The platform also includes out-of-the-box and customizable machine learning algorithms for advanced forecasting and analytics. Moreover, because GoodData can process large, complex, and siloed datasets, this BI solution can scale to handle virtually any size demand.
Popular Use Cases
Bring all your GoodData data to Amazon Redshift
Load your GoodData data to Google BigQuery
ETL all your GoodData data to Snowflake
Move your GoodData data to MySQL
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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.
GoodData's End Points
GoodData Analytics, Dashboards, Visualizations
GoodData features dashboards that you can easily embed into your desktop or mobile applications, so your business insights and visualizations are accessible wherever you need them to be. The platform includes customizable, interactive visualizations and drag-and-drop analytics and discovery tools. It also features easy-to-set-up machine-learning algorithms for forecasting and better decision-making.
GoodData Embedded Analytics
GoodData allows you to tailor each of your customer's experiences with personalized, embedded analytics and data models. By putting more power into your customers' hands, the platform lets your more tech-savvy users design and publish their own reports, dashboards, and visual presentations. Moreover, after developing new analytical features, you can distribute updates seamlessly across tens of thousands of users at once, or you can centrally manage distribution and customize the updates and features that different product audiences receive.
GoodData Data Ingestion at Scale
GoodData's fault-tolerant data pipeline enables high-speed ingestion of terabytes of information for tens of thousands of users. The platform also helps you respond to issues through constant monitoring and alerts that integrate with your incident response systems. GoodData's pre-built modules for data ingestion, transformation, and distribution offer time-saving advantages. Set up your data transformations in SQL and JDBC, and modify GoodData's pre-built modules with Python, Ruby, and Java SDKs.
GoodData is an enterprise-level solution that offers reliable, real-time processing and insights at scale — no matter how many clients — with a capacity to handle virtually any size dataset.
GoodData Security and Compliance
GoodData offers the latest in data security technologies and risk management features so any size company can meet its industry's compliance and information security requirements. GoodData's Security Shield system is the platform's basic-level security offering, which adheres to standard best practices for cloud-based data protection, including ISO 27001:2013 compliance, GDPR compliance, and SOC2 Type II. Meanwhile, Enterprise Shield Security is GoodData's higher-level security offering, which offers protection for enterprises handling extra-sensitive and/or strictly-regulated information.