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Description

A Kudu cluster comprises tables that resemble those found in traditional relational (SQL) databases. These tables can range from a straightforward binary key and value structure to intricate designs featuring hundreds of strongly-typed attributes. Similar to SQL tables, each Kudu table is defined by a primary key, which consists of one or more columns; this could be a single unique user identifier or a composite key such as a (host, metric, timestamp) combination tailored for time-series data from machines. The primary key allows for quick reading, updating, or deletion of rows. The straightforward data model of Kudu facilitates the migration of legacy applications as well as the development of new ones, eliminating concerns about encoding data into binary formats or navigating through cumbersome JSON databases. Additionally, tables in Kudu are self-describing, enabling the use of standard analysis tools like SQL engines or Spark. With user-friendly APIs, Kudu ensures that developers can easily integrate and manipulate their data. This approach not only streamlines data management but also enhances overall efficiency in data processing tasks.

Description

What happens when your company's CRM software fails to connect with any current customer survey platforms? With Gridoc, you can seamlessly utilize your chosen customer survey service and effortlessly merge the gathered data with your existing CRM database by employing the Join Tables feature. Your company is currently working with several contractors conducting market research, but despite your clear instructions on the desired data format, each contractor submits their reports with a slightly varied order of columns in their spreadsheets. Fortunately, Gridoc allows you to integrate these spreadsheets into a single cohesive table through the Combine Tables feature, which accurately recognizes and aligns columns from various files, thus preventing the tedious and error-prone task of manual copying and data correction. Additionally, as your next marketing campaign requires a comprehensive list of purchased products per customer, you might find the e-shop's reporting feature to be cumbersome and lacking in functionality. Conversely, you can easily obtain a list of transactions directly from the e-shop's admin interface, providing a more efficient solution for your data needs. This approach not only streamlines the data collection process but also enhances the accuracy of the information used in your marketing strategies.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Apache Flink
Apache NiFi
Apache Spark
BigBI
Cloudera Data Warehouse
E-MapReduce
Hadoop

Integrations

Apache Flink
Apache NiFi
Apache Spark
BigBI
Cloudera Data Warehouse
E-MapReduce
Hadoop

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

The Apache Software Foundation

Founded

1999

Country

United States

Website

kudu.apache.org/overview.html

Vendor Details

Company Name

Gridoc

Founded

2013

Country

Slovakia

Website

gridoc.com

Product Features

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

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