Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
Greenplum Database® stands out as a sophisticated, comprehensive, and open-source data warehouse solution. It excels in providing swift and robust analytics on data volumes that reach petabyte scales. Designed specifically for big data analytics, Greenplum Database is driven by a highly advanced cost-based query optimizer that ensures exceptional performance for analytical queries on extensive data sets. This project operates under the Apache 2 license, and we extend our gratitude to all current contributors while inviting new ones to join our efforts. In the Greenplum Database community, every contribution is valued, regardless of its size, and we actively encourage diverse forms of involvement. This platform serves as an open-source, massively parallel data environment tailored for analytics, machine learning, and artificial intelligence applications. Users can swiftly develop and implement models aimed at tackling complex challenges in fields such as cybersecurity, predictive maintenance, risk management, and fraud detection, among others. Dive into the experience of a fully integrated, feature-rich open-source analytics platform that empowers innovation.
API Access
Has API
No
API Access
Has API
No
Integrations
Docker
Yes
Algolia
Yes
Apache Superset
No
ConvertFlow
Yes
DBHawk
No
DataGrip
No
DbVisualizer
No
Hadoop
No
Lyftrondata
No
Peaka
No
Integrations
Docker
Yes
Algolia
No
Apache Superset
Yes
ConvertFlow
No
DBHawk
Yes
DataGrip
Yes
DbVisualizer
Yes
Hadoop
Yes
Lyftrondata
Yes
Peaka
Yes
Pricing Details
$0.27 per hour
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
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
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
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
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Citus Data
Country
United States
Website
www.citusdata.com
Vendor Details
Company Name
Greenplum Database
Founded
2003
Country
United States
Website
greenplum.org
Product Features
Product Features
Database
Backup and Recovery
No
Creation / Development
No
Data Migration
No
Data Replication
No
Data Search
No
Data Security
No
Database Conversion
No
Mobile Access
No
Monitoring
No
NOSQL
No
Performance Analysis
No
Queries
No
Relational Interface
No
Virtualization
No