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What is IBM StreamSets?

IBM® StreamSets empowers users to design and manage intelligent streaming data pipelines through a user-friendly graphical interface, making it easier to integrate data seamlessly in both hybrid and multicloud settings. Renowned global organizations leverage IBM StreamSets to manage millions of data pipelines, facilitating modern analytics and the development of smart applications. This platform significantly reduces data staleness while providing real-time information at scale, efficiently processing millions of records across thousands of pipelines within seconds. The drag-and-drop processors are designed to automatically identify and adapt to data drift, ensuring that your data pipelines remain resilient to unexpected changes. Users can create streaming pipelines to ingest structured, semi-structured, or unstructured data, efficiently delivering it to various destinations while maintaining high performance and reliability. Additionally, the system's flexibility allows for rapid adjustments to evolving data needs, making it an invaluable tool for data management in today's dynamic environments.

What is Informatica Data Engineering?

Efficiently ingesting, preparing, and managing data pipelines at scale is critical for cloud-based AI and analytics. Informatica's extensive data engineering suite provides users with a comprehensive array of tools essential for executing large-scale data engineering tasks that facilitate AI and analytical insights, incorporating features like advanced data integration, quality assurance, streaming capabilities, data masking, and preparation functionalities. Through CLAIRE®-driven automation, users can rapidly create intelligent data pipelines that incorporate automatic change data capture (CDC), enabling the ingestion of numerous databases and millions of files along with streaming events. This methodology significantly accelerates the return on investment by facilitating self-service access to trustworthy, high-quality data. Users can gain authentic perspectives on Informatica's data engineering solutions from reliable industry peers. Moreover, reference architectures tailored for sustainable data engineering practices can be explored to enhance efficiency. By adopting AI-driven data engineering in the cloud, organizations can guarantee that their analysts and data scientists have the reliable, high-quality data necessary for effectively transforming their business operations. This comprehensive strategy not only simplifies data management but also empowers teams to confidently make data-driven decisions, ultimately paving the way for innovative business solutions. In conclusion, leveraging such advanced tools and practices positions organizations to thrive in an increasingly data-centric landscape.

Media

Media

Integrations Supported

Amazon Redshift
Amazon S3
Amazon Simple Queue Service (SQS)
Apache Cassandra
Azure Data Lake Storage
Azure Industrial IoT
Delta Lake
Elasticsearch
FairCom DB
FairCom EDGE
FileTrail Records Management
HPE Ezmeral Data Fabric
Hadoop
MongoDB
MySQL
PostgreSQL
Redis
SAP HANA
Salesforce
Splunk Cloud Platform

Integrations Supported

Amazon Redshift
Amazon S3
Amazon Simple Queue Service (SQS)
Apache Cassandra
Azure Data Lake Storage
Azure Industrial IoT
Delta Lake
Elasticsearch
FairCom DB
FairCom EDGE
FileTrail Records Management
HPE Ezmeral Data Fabric
Hadoop
MongoDB
MySQL
PostgreSQL
Redis
SAP HANA
Salesforce
Splunk Cloud Platform

API Availability

Has API

API Availability

Has API

Pricing Information

$1000 per month
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/products/streamsets

Company Facts

Organization Name

Informatica

Date Founded

1993

Company Location

United States

Company Website

www.informatica.com/products/big-data.html

Categories and Features

DevOps

Approval Workflow
Dashboard
KPIs
Policy Management
Portfolio Management
Prioritization
Release Management
Timeline Management
Troubleshooting Reports

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

Categories and Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

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