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Description
Citus enhances the beloved Postgres experience by integrating the capability of distributed tables, while remaining fully open source. It now supports both schema-based and row-based sharding, alongside compatibility with Postgres 16. You can scale Postgres effectively by distributing both data and queries, starting with a single Citus node and seamlessly adding more nodes and rebalancing shards as your needs expand. By utilizing parallelism, maintaining a larger dataset in memory, increasing I/O bandwidth, and employing columnar compression, you can significantly accelerate query performance by up to 300 times or even higher. As an extension rather than a fork, Citus works with the latest versions of Postgres, allowing you to utilize your existing SQL tools and build on your Postgres knowledge. Additionally, you can alleviate infrastructure challenges by managing both transactional and analytical tasks within a single database system. Citus is available for free download as open source, giving you the option to self-manage it while actively contributing to its development through GitHub. Shift your focus from database concerns to application development by running your applications on Citus within the Azure Cosmos DB for PostgreSQL environment, making your workflow more efficient.
Description
PostgresML serves as a comprehensive platform integrated within a PostgreSQL extension, allowing users to construct models that are not only simpler and faster but also more scalable directly within their database environment. Users can delve into the SDK and utilize open-source models available in our hosted database for experimentation. The platform enables a seamless automation of the entire process, from generating embeddings to indexing and querying, which facilitates the creation of efficient knowledge-based chatbots. By utilizing various natural language processing and machine learning techniques, including vector search and personalized embeddings, users can enhance their search capabilities significantly. Additionally, it empowers businesses to analyze historical data through time series forecasting, thereby unearthing vital insights. With the capability to develop both statistical and predictive models, users can harness the full potential of SQL alongside numerous regression algorithms. The integration of machine learning at the database level allows for quicker result retrieval and more effective fraud detection. By abstracting the complexities of data management throughout the machine learning and AI lifecycle, PostgresML permits users to execute machine learning and large language models directly on a PostgreSQL database, making it a robust tool for data-driven decision-making. Ultimately, this innovative approach streamlines processes and fosters a more efficient use of data resources.
API Access
Has API
No
API Access
Has API
Yes
Integrations
PostgreSQL
Yes
Azure Cosmos DB
Yes
C++
No
ChatGPT
No
DBeaver Community
No
Elixir
No
Go
No
Java
No
Llama
No
Llama 3.2
No
Integrations
PostgreSQL
Yes
Azure Cosmos DB
No
C++
Yes
ChatGPT
Yes
DBeaver Community
Yes
Elixir
Yes
Go
Yes
Java
Yes
Llama
Yes
Llama 3.2
Yes
Pricing Details
$0.27 per hour
Free Trial
No
Free Version
Yes
Pricing Details
$.60 per hour
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Citus Data
Country
United States
Website
www.citusdata.com
Vendor Details
Company Name
PostgresML
Website
postgresml.org
