Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Apache Phoenix provides low-latency OLTP and operational analytics on Hadoop by merging the advantages of traditional SQL with the flexibility of NoSQL. It utilizes HBase as its underlying storage, offering full ACID transaction support alongside late-bound, schema-on-read capabilities. Fully compatible with other Hadoop ecosystem tools such as Spark, Hive, Pig, Flume, and MapReduce, it establishes itself as a reliable data platform for OLTP and operational analytics through well-defined, industry-standard APIs. When a SQL query is executed, Apache Phoenix converts it into a series of HBase scans, managing these scans to deliver standard JDBC result sets seamlessly. The framework's direct interaction with the HBase API, along with the implementation of coprocessors and custom filters, enables performance metrics that can reach milliseconds for simple queries and seconds for larger datasets containing tens of millions of rows. This efficiency positions Apache Phoenix as a formidable choice for businesses looking to enhance their data processing capabilities in a Big Data environment.
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
Yes
API Access
Has API
Yes
Integrations
Apache HBase
Yes
Hadoop
Yes
3forge
Yes
Amazon EMR
Yes
Amazon S3
No
Apache Flume
Yes
Apache Hive
Yes
Apache Spark
Yes
Azure Blob Storage
No
Data Sentinel
Yes
Integrations
Apache HBase
Yes
Hadoop
Yes
3forge
No
Amazon EMR
No
Amazon S3
Yes
Apache Flume
No
Apache Hive
No
Apache Spark
No
Azure Blob Storage
Yes
Data Sentinel
No
Pricing Details
Free
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
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
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
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Apache Software Foundation
Website
phoenix.apache.org
Vendor Details
Company Name
EDB
Founded
2004
Country
United States
Website
warehouse-pg.io
Product Features
Relational Database
ACID Compliance
No
Data Failure Recovery
No
Multi-Platform
No
Referential Integrity
No
SQL DDL Support
No
SQL DML Support
No
System Catalog
No
Unicode Support
No
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