Securely integrate Vertica Analytics Platform with Google Hotel Price
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 Google Hotel Price
Google Hotel Price allows users to search for hotels right on Google and in Google Maps, getting a list of hotels with prices, photos, reviews, and street view panoramas. Connecting your properties to this service can help you increase your traffic, expand your reach, and improve your reputation and user reviews.
Popular Use Cases
Bring all your Google Hotel Price data to Amazon Redshift
Load your Google Hotel Price data to Google BigQuery
ETL all your Google Hotel Price data to Snowflake
Move your Google Hotel Price data to MySQL
Integrate Vertica Analytics Platform With Google Hotel Price Today
Free 14-day trial. Easy setup. Cancel any time.
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.
Google Hotel Price's End Points
Google Hotel Price Reports
Specify a report you want to receive or retrieve a list of available reports. This can give you a solid understanding of your numbers and help you develop long-term insights.
Google Hotel Price Bids
List your submitted bids, including information about each bid and that bid’s multipliers. This information can help you see if you are bidding competitively and determine how to drive more customer volume to your properties.
Google Hotel Price Scorecard
Retrieve values displayed in the Hotel Ads Center scorecard view. This includes account-specific data, price accuracy scores, performance stats, opportunity stats, and more.
Google Hotel Price Feed Status
Get a report of your feeds so that you can have an updated understanding of your availability, prices, and hotels. Additionally, get insight into any errors or warnings that Google encountered so you can identify and fix issues ASAP.
Google Hotel Price Prices
Retrieve itinerary - check-in dates, length of stay, room rates, etc. - and pricing data for a particular property. This data can help you understand customer behavior, seasonal changes, and more.
Google Hotel Price Hotels
View your Hotel List Feed to see valid hotels and hotels that aren’t indexed. Use this information to clean up your hotel list and fix any issues, including duplicate data, ambiguous or invalid names, etc.