Securely integrate Vertica Analytics Platform with Stripe
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.
Stripe is a SaaS payment management tool. It is built to be an all-in-one payment solution for any business, whether that business offers an on-demand service, traditional product sales, or subscription-based services. Stripe’s tools are designed to help users with a variety of tasks related to running those businesses, including: issuing refunds, processing orders, and managing different subscriptions.
Popular Use Cases
Bring all your Stripe data to Amazon Redshift
Load your Stripe data to Google BigQuery
ETL all your Stripe data to Snowflake
Move your Stripe 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.
Stripe's End Points
Retrieve data from all your customer transactions, which provides basic details about the customer, such as their name, address, and email, in addition to data about the charge itself, such as if it was accepted, disputed, refunded, etc.
View or create data about new and existing customers, which allows you to track recurring charges, subscriptions, and multiple purchases. This can, in turn, help you to monitor a customer’s transaction history throughout their lifecycle with your company.
Retrieve any automatically recorded event that occurs on your account, whether it’s a charge, subscription, failed invoice payment, or anything else of note. This allows you to have current, up-to-date data about what is happening on your account at any given moment.
Monitor an invoice, which is created as part of a recurring payment on Stripe. This returns data on the charged amount, whether the invoice was successful, how many attempts the invoice has made to collect the money, and which subscriptions are linked to that invoice, if applicable.
Collect data on different subscription plans that you have, which includes the cost of the plan, how and when it is billed, and the plan’s trial period. You can then integrate the plan data with your subscription or customer data to get a deeper view of the sales performance of various plans.
Track which clients are subscribed to which plans, as well as when they subscribed, when they canceled, and how many users they are subscribed with. This field also allows you to track charges associated with those subscriptions so that you can monitor the revenue they generate.