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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
Yes
API Access
Has API
No
Integrations
Apache Flink
Yes
Apache NiFi
Yes
Apache Spark
Yes
BigBI
Yes
Cloudera Data Warehouse
Yes
E-MapReduce
Yes
Hadoop
Yes
Integrations
Apache Flink
No
Apache NiFi
No
Apache Spark
No
BigBI
No
Cloudera Data Warehouse
No
E-MapReduce
No
Hadoop
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
Yes
Deployment
Web-Based
No
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
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
Product Features
Data Management
Customer Data
Yes
Data Analysis
Yes
Data Capture
No
Data Integration
No
Data Migration
Yes
Data Quality Control
Yes
Data Security
Yes
Information Governance
No
Master Data Management
Yes
Match & Merge
Yes
