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features
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support

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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

Secure your connection using SSL encryption or establish a tunnel via SSH for enhanced safety. Store your connection password securely, as Beekeeper Studio will ensure it is encrypted for your protection. The integrated editor features syntax highlighting and auto-complete capabilities for your tables, allowing you to work efficiently and effortlessly. You can open multiple tabs simultaneously, facilitating a seamless workflow without the need to toggle between different windows. Each table's DDL and data views are conveniently placed in their own tabs as well! Furthermore, you can easily save and categorize frequently used queries, making them readily accessible across all your connections. With Beekeeper's SQL table creator, you can swiftly create, modify, and remove table columns in just a few clicks. Exporting a table to formats such as CSV, JSON, JSONL, or SQL is also simplified, allowing you to do so with minimal effort. Additionally, you have the option to apply filters during the export process, ensuring you retrieve only the specific data you require. This flexibility enhances productivity and streamlines your data management tasks.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Apache Flink Yes 
Apache NiFi Yes 
Apache Spark Yes 
BigBI Yes 
Cloudera Data Warehouse Yes 
E-MapReduce Yes 
Hadoop Yes 
MySQL No 
PostgreSQL No 
SQL Server No 
SQLite No 

Integrations

Apache Flink No 
Apache NiFi No 
Apache Spark No 
BigBI No 
Cloudera Data Warehouse No 
E-MapReduce No 
Hadoop No 
MySQL Yes 
PostgreSQL Yes 
SQL Server Yes 
SQLite Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$7 per month
Free Trial Yes 
Free Version No 

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 No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
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) No 
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

Beekeeper Studio

Website

www.beekeeperstudio.io

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