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
WarehousePG is a powerful open-source database designed for extensive data warehousing, business intelligence, and analytics, utilizing massively parallel processing (MPP) to enhance performance. Built on the foundation of PostgreSQL, it efficiently allocates data and processing tasks across a network of coordinator and segment servers. Users familiar with SQL can easily connect via various PostgreSQL-compatible clients and interfaces, such as psql, JDBC, ODBC, and libpq. Its features include optimized storage options, whether row- or column-oriented, table partitioning, and the ability to load data in parallel through external tables. Additionally, it offers robust workload and resource management, advanced query planning using GPORCA, and ensures high availability through mirroring of both coordinator and segment servers. The Platform Extension Framework (PXF) enables WarehousePG to interact with and manipulate external data from diverse sources, including Hadoop, object storage systems, and SQL databases accessible via JDBC. This platform is well-suited for analytical warehousing and business intelligence tasks, supporting cluster configurations on Linux in both on-premises and cloud environments. Furthermore, its scalability makes it an ideal choice for organizations looking to leverage large datasets for insightful decision-making.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Amazon S3
No
Apache HBase
No
Azure Blob Storage
No
Azure Cosmos DB
Yes
CentOS
Yes
Cisco CX Cloud
Yes
ConvertFlow
Yes
CrossMigrateDB
Yes
Docker
Yes
EDB Postgres AI
No
Integrations
Amazon S3
Yes
Apache HBase
Yes
Azure Blob Storage
Yes
Azure Cosmos DB
No
CentOS
No
Cisco CX Cloud
No
ConvertFlow
No
CrossMigrateDB
No
Docker
No
EDB Postgres AI
Yes
Pricing Details
$0.27 per hour
Free Trial
No
Free Version
Yes
Pricing Details
$0
The WarehousePG project is free and open source.
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
No
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
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)
No
Online Support
No
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
EDB
Founded
2004
Country
United States
Website
warehouse-pg.io
Product Features
Product Features
Data Warehouse
Ad hoc Query
No
Analytics
No
Data Integration
No
Data Migration
No
Data Quality Control
No
ETL - Extract / Transfer / Load
No
In-Memory Processing
No
Match & Merge
No
Alternatives
Alternatives
No Alternatives