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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 DataKitchen DataOps Automation?

DataKitchen is a data quality, observability, and DataOps automation platform developed to help organizations manage reliable data pipelines and analytics processes. The platform combines automated testing, operational monitoring, workflow orchestration, and deployment management across existing enterprise data infrastructure. Its DataOps Data Quality TestGen product profiles database tables and columns to identify data characteristics, detect anomalies, and automatically generate validation tests. TestGen analyzes 55 column characteristics and supports 34 automatically generated test types, along with configurable business rules and custom SQL validations. Data quality monitoring helps teams identify issues involving missing values, duplicate records, schema changes, unusual data distributions, and other conditions that may affect analytics accuracy. DataOps Process Observability monitors the complete journey of data from source systems through transformation pipelines and analytical applications to downstream consumers. Its unified event monitoring capabilities collect execution statuses, operational metrics, logs, and test outcomes from connected data tools to provide visibility into pipeline health. Rule-based alerting notifies teams about failures, late data arrivals, and test regressions through integrations with email, Slack, Microsoft Teams, and Jira. DataOps Automation enables organizations to coordinate pipelines across different tools, create isolated development environments, reuse workflow components, and automate deployment from development through production. The platform supports integrations with Snowflake, Databricks, BigQuery, Amazon Redshift, PostgreSQL, Airflow, dbt, Azure Data Factory, and other data engineering technologies.

Media

Media

Integrations Supported

PostgreSQL
Snowflake
Amazon Redshift
Azure Industrial IoT
Couchbase
CrateDB
Delta Lake
Elasticsearch
HPE Ezmeral Data Fabric
MongoDB
MySQL
Redis
SAP HANA
Salesforce
Splunk Cloud Platform

Integrations Supported

PostgreSQL
Snowflake
Docker
Git
GitHub
Google Cloud BigQuery
Jenkins

API Availability

Has API

API Availability

Pricing Information

$1000 per month
5 active jobs
5 users
50 published pipelines
99.9% uptime
Email Support (Business hours M-F)
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Not specified

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/products/streamsets

Company Facts

Organization Name

DataKitchen

Date Founded

2013

Company Location

United States

Company Website

datakitchen.io

Categories and Features

Data Integration

Not specified

Data Pipeline

Not specified

DataOps

Not specified

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

Automated Testing

Not specified

Data Observability

Not specified

Data Pipeline

Not specified

Data Quality

Not specified

DataOps

Not specified

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