Connect Vertica Analytics Platform to Mode

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Vertica Analytics Platform
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Mode
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About Vertica Analytics Platform

Extract, transform, and load data to Vertica. Ingest data from Vertica and load to other destinations.

About Mode

As an advanced, high-speed data analytics platform, Mode helps you understand the information in your data warehouses. As a hybrid solution Mode lets (1) data teams customize queries and visualizations in Python, SQL, or R; and (2) empowers non-tech-savvy users to dive into visualizations and explore live-updating reports to get the data they need.

Popular Use Cases

Bring all your Mode data to Amazon Redshift

Load your Mode data to Google BigQuery

ETL all your Mode data to Snowflake

Move your Mode data to MySQL

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, Integrate.io's ETL-as-a-service tool offers a native integration to connect with Vertica.

Mode's End Points

Mode White-Label Embeds and Visualizations
Mode's White-Label Embeds allow you to integrate customized, interactive visualizations, and analytics into your applications — so your customers can access powerful reporting that seamlessly blends with your apps. White-Label Embeds also secure your data by ensuring that specific customers see appropriate information only. Lastly, Mode includes pre-built charts and the ability customize your visualizations in JavaScript, HTML, and CCS.
Mode SQL Editor
Mode's SQL editor features a schema browser to explore the tables and columns of your connected data sources. It also has an autocomplete function to assist with query writing, a query history to browse and reuse old queries, and advanced logic tools for creating loops, IF statements, and more.
Mode Helix Data Engine
The technology behind Mode's analytics solution is Helix, a high-performance in-memory data engine that combines modern drag-and-drop business intelligence tools with a code-first (SQL, Python, R) data science platform to offer an instantly responsive user experience. Mode streams query results into the Helix data engine to reduce database load, provide quick responsiveness, and give users the ability to visually navigate as much as 10 gigabytes of data.
Mode Dashboard Features
Powered by SQL, Python, and R, Mode dashboards display automatically-refreshing metrics without the need for proprietary tools. Customize your dashboards the way you want, with on-brand reporting and interactive features to facilitate collaboration with others across your organization.
Mode Native Python and R Notebooks
Mode features native Python and R Notebooks. This allows you to query in SQL, send the results to a dataframe in R or pandas, and conveniently access them in the platform's native Notebook. At the same time, a sidebar provides tips, shortcuts, and documentation to help you get the most of these features.

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Integrates With

8x8
AS400
AdRoll
Aftership
Airtable
AlloyDB
Amazon Aurora
Amazon Kinesis
Amazon RDS
Amazon Redshift
Amazon S3
Amplitude
AppsFlyer
Asana
Coming Soon
AskNicely
Atlassian
Autopilot
Azure Synapse Analytics
Base CRM
Basecamp
BigCommerce
Bill.com
Coming Soon
Box
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Braintree
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Branch
Buffer
CallRail
Campaign Monitor
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Cassandra
ChartMogul
Chartio
Clearbit
CleverTap
Close.io
CloudTrail
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Contentful
Cratejoy
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Crunchbase
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Customer.io
Delighted
Domo
DoubleClick Bid Manager
DoubleClick Campaign Manager
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Drift
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Drip
Dundas BI
Elasticsearch
Eloqua
Coming Soon
Eventbrite
FTPS
Facebook Ads
Freshdesk
Fullstory
GitHub
GitLab
GoToWebinar
GoodData
Google Ads
Google Analytics
Google BigQuery
Google Cloud SQL for MySQL
Google Cloud SQL for PostgreSQL
Google Cloud Spanner
Google Cloud Storage
Google Drive
Google Hotel Price
Google My Business
Google Sheets
HDFS
Coming Soon
Harvest
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Heap
Help Scout
Heroku Connect
Heroku Postgres
HubSpot
IBM DB2
Intercom
Invoiced
Coming Soon
Iterable
Jaspersoft
Jira
LinkedIn
Listrak
LivePerson
Loggly
Looker
MS SQL
Magento
MailChimp
Mailgun
MariaDB
Marketo
MemSQL
Microsoft Ads
Microsoft Azure Blob Storage
Microsoft Azure SQL Database
Mixpanel
Mode
MongoDB
MongoDB Atlas
MySQL
NetSuite
Oracle
Oracle Responsys
Outbrain
Papertrail
Pendo
Periscope Data
Pinterest
Pipedrive
PostgreSQL
QlikView
Coming Soon
QuickBooks
RESTful API
Recurly
Revinate
SFTP
SFTP To Go
Salesforce
Salesforce Marketing Cloud
Salesforce Pardot
Segment
SendGrid
ShipStation
Shippo
Shopify
Slack
Snapchat Ads
Snowflake
Coming Soon
Square
Stamped.io
Stripe
Taboola
Trello
Twilio
UserVoice
Wrike
Xero
Yahoo Gemini
Yotpo
YouTube
Zendesk
Zendesk Chat
Zuora
e-conomic

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