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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
Integrate the TableFlow import functionality directly into your application with minimal coding effort. Users can conveniently upload CSV files, map their columns, and address any errors to finalize the import process. Developers can then access the refined JSON data through the frontend SDK or the TableFlow API. This allows your engineering team to dedicate more time to enhancing core product features and innovations. Speed up the onboarding process for new customers with TableFlow’s efficient data import system. Eliminate the burden of manual data cleaning by utilizing advanced error detection and automatic correction capabilities. You can embed a fully customizable modal in your app using our frontend SDKs. The importer can be easily configured and tailored to your needs without any coding. Adjust the import process to seamlessly align with your application’s design. The system can automatically identify header rows and map the corresponding columns accordingly. You can impose requirements on all incoming data, enabling the import of millions of rows in mere seconds. With TableFlow, the open-source CSV importer, you can significantly accelerate the onboarding of customer data and enhance user satisfaction in the process. Ensure a smoother transition for your users by providing them with a reliable and efficient data import experience.
API Access
Has API
API Access
Has API
Integrations
Apache Flink
Apache NiFi
Apache Spark
BigBI
CSS
E-MapReduce
HTML
Hadoop
JSON
JavaScript
Integrations
Apache Flink
Apache NiFi
Apache Spark
BigBI
CSS
E-MapReduce
HTML
Hadoop
JSON
JavaScript
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$99 per month
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
TableFlow
Website
tableflow.com
Product Features
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