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What is Citus?

Citus enriches the widely appreciated Postgres experience by offering distributed table capabilities while being entirely open source. It now accommodates both schema-based and row-based sharding, ensuring compatibility with Postgres 16. You can effectively scale Postgres by distributing data and queries, starting with a single Citus node and smoothly incorporating additional nodes and rebalancing shards as your requirements grow. By leveraging parallelism, keeping a larger dataset in memory, boosting I/O bandwidth, and using columnar compression, query performance can be significantly enhanced, achieving speeds up to 300 times or even more. As an extension rather than a separate fork, Citus remains compatible with the latest Postgres versions, allowing you to leverage your existing SQL expertise and tools. Furthermore, it enables you to address infrastructure challenges by managing both transactional and analytical workloads within one database system. Available for free as open source, Citus allows for self-management while also inviting contributions to its development via GitHub. Transitioning your focus from database management to application development becomes easier as you run your applications on Citus within the Azure Cosmos DB for PostgreSQL environment, thus streamlining your workflow. This integration not only boosts efficiency but also empowers developers to harness the full potential of scalable, high-performance database solutions.

What is Apache Kudu?

A Kudu cluster organizes its information into tables that are similar to those in conventional relational databases. These tables can vary from simple binary key-value pairs to complex designs that contain hundreds of unique, strongly-typed attributes. Each table possesses a primary key made up of one or more columns, which may consist of a single column like a unique user ID, or a composite key such as a tuple of (host, metric, timestamp), often found in machine time-series databases. The primary key allows for quick access, modification, or deletion of rows, which ensures efficient data management. Kudu's straightforward data model simplifies the process of migrating legacy systems or developing new applications without the need to encode data into binary formats or interpret complex databases filled with hard-to-read JSON. Moreover, the tables are self-describing, enabling users to utilize widely-used tools like SQL engines or Spark for data analysis tasks. The user-friendly APIs that Kudu offers further increase its accessibility for developers. Consequently, Kudu not only streamlines data management but also preserves a solid structural integrity, making it an attractive choice for various applications. This combination of features positions Kudu as a versatile solution for modern data handling challenges.

Media

Media

Integrations Supported

Algolia
Azure Cosmos DB
Cisco CX Cloud
ConvertFlow
CrossMigrateDB
Fedora
Freshworks Neo
GitHub
MixRank
PEX
PostgreSQL
Salesloft
Ubuntu

Integrations Supported

Apache Flink
Apache NiFi
BigBI
Cloudera Data Warehouse
E-MapReduce
Hadoop

API Availability

API Availability

Has API

Pricing Information

$0.27 per hour
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem

Supported Platforms

Windows
Mac
On-Prem
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Citus Data

Company Location

United States

Company Website

www.citusdata.com

Company Facts

Organization Name

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

kudu.apache.org/overview.html

Categories and Features

Distributed Databases

Not specified

OLAP Databases

Not specified

Categories and Features

Columnar Databases

Not specified

Distributed Databases

Not specified

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