How to join Amazon S3 and IBM Netezza

Discover how to join Amazon S3 with IBM Netezza for integrated analysis.

WITH DATA VIRTUALITY PIPES
Replicate Amazon S3 and IBM Netezza data into one target storage and analyze it with your BI Tool.
How to join Amazon S3 and IBM Netezza with Pipes


About Amazon S3

Amazon Simple Storage Service (Amazon S3) is an object store with a simple web service interface. Users can retrieve and store any amount of data from anywhere in the Internet. Customers use Amazon S3 as primary storage for cloud-native applications, mass repositories, or datalake, for analysis, as a backup and recovery target, as well as disaster recovery and serverless data processing.

About IBM Netezza

IBM Netezza designs and markets advanced data warehouse appliances for analytics applications. Use cases for IBM Netezza include business intelligence, data warehousing, business continuity planning and predictive analytics. The Netezza SQL commands support the standard grammar (SQL-92). The purpose-built, embedded, advanced analytics platform IBM Netezza Analytics helps client's analytics to meet their business demands.

MOVE YOUR DATA WITH PIPES

Pipes allows you to connect to Amazon S3, IBM Netezza and more than 200 other cloud services and databases. Automate your data workflows with data pipelines.

DATA VIRTUALITY OFFERS TWO PIPES SOLUTIONS

depending on your needs.

Pipes

Easy and reliable data replication in the cloud

Pipes enables you to move data from any data source to your target storage or data warehouse on schedule. Integrate your data with just a few clicks and without any coding.

Pipes Professional

Advanced data replication hosted in the cloud or on-premises

Pipes Professional enables you to transform and model your data with SQL before replication. Customize your data pipelines and build data models across sources in 80% less time.

Pipes Professional features include:

  • Cloud/On-Premises Hosting
  • Complex Data Transformations
  • Advanced Jobs & Schedules
  • Multiple Target Storages
  • Custom Extraction Definitions
  • Job Dependencies
  • SQL Modelling Layer
  • Complex Replication Types
  • Custom Job Triggers
Your future with automated data workflows is only a few clicks away.