Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
Introducing a robust cross-platform columnar database designed for high-performance historical time-series data, which includes:
- A compute engine optimized for in-memory operations
- A streaming processor that functions in real time
- A powerful query and programming language known as q
Kdb+ drives the kdb Insights portfolio and KDB.AI, offering advanced time-focused data analysis and generative AI functionalities to many of the world's top enterprises. Recognized for its unparalleled speed, kdb+ has been independently benchmarked* as the leading in-memory columnar analytics database, providing exceptional benefits for organizations confronting complex data challenges. This innovative solution significantly enhances decision-making capabilities, enabling businesses to adeptly respond to the ever-evolving data landscape. By leveraging kdb+, companies can gain deeper insights that lead to more informed strategies.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Apache Flink
Yes
Apache NiFi
Yes
Apache Spark
Yes
App Orchid
No
BigBI
Yes
Cloudera Data Warehouse
Yes
E-MapReduce
Yes
Hadoop
Yes
KDB.AI
No
PubSub+ Platform
No
Integrations
Apache Flink
No
Apache NiFi
No
Apache Spark
No
App Orchid
Yes
BigBI
No
Cloudera Data Warehouse
No
E-MapReduce
No
Hadoop
No
KDB.AI
Yes
PubSub+ Platform
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
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
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
No
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
KX Systems
Founded
1993
Country
United Kingdom
Website
kx.com/products/kdb/