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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
Yes
API Access
Has API
Yes
Integrations
Apache Flink
Yes
Apache NiFi
Yes
Apache Spark
Yes
BigBI
Yes
CSS
No
Cloudera Data Warehouse
Yes
E-MapReduce
Yes
HTML
No
Hadoop
Yes
JSON
No
Integrations
Apache Flink
No
Apache NiFi
No
Apache Spark
No
BigBI
No
CSS
Yes
Cloudera Data Warehouse
No
E-MapReduce
No
HTML
Yes
Hadoop
No
JSON
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$99 per month
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
No
Live Rep (24/7)
Yes
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
TableFlow
Website
tableflow.com
Product Features
Product Features
Data Management
Customer Data
No
Data Analysis
No
Data Capture
No
Data Integration
No
Data Migration
No
Data Quality Control
No
Data Security
No
Information Governance
No
Master Data Management
No
Match & Merge
No
