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Description
Data processing that integrates both streaming and batch operations while being serverless, efficient, and budget-friendly. It offers a fully managed service for data processing, ensuring seamless automation in the provisioning and administration of resources. With horizontal autoscaling capabilities, worker resources can be adjusted dynamically to enhance overall resource efficiency. The innovation is driven by the open-source community, particularly through the Apache Beam SDK. This platform guarantees reliable and consistent processing with exactly-once semantics. Dataflow accelerates the development of streaming data pipelines, significantly reducing data latency in the process. By adopting a serverless model, teams can devote their efforts to programming rather than the complexities of managing server clusters, effectively eliminating the operational burdens typically associated with data engineering tasks. Additionally, Dataflow’s automated resource management not only minimizes latency but also optimizes utilization, ensuring that teams can operate with maximum efficiency. Furthermore, this approach promotes a collaborative environment where developers can focus on building robust applications without the distraction of underlying infrastructure concerns.
Description
IBM Streams analyzes a diverse array of streaming data, including unstructured text, video, audio, geospatial data, and sensor inputs, enabling organizations to identify opportunities and mitigate risks while making swift decisions. By leveraging IBM® Streams, users can transform rapidly changing data into meaningful insights. This platform evaluates various forms of streaming data, empowering organizations to recognize trends and threats as they arise. When integrated with other capabilities of IBM Cloud Pak® for Data, which is founded on a flexible and open architecture, it enhances the collaborative efforts of data scientists in developing models to apply to stream flows. Furthermore, it facilitates the real-time analysis of vast datasets, ensuring that deriving actionable value from your data has never been more straightforward. With these tools, organizations can harness the full potential of their data streams for improved outcomes.
API Access
Has API
API Access
Has API
Integrations
CData Connect
DataBuck
Google Cloud Bigtable
Google Cloud Composer
Google Cloud Dataplex
Google Cloud Datastream
Google Cloud IoT Core
Google Cloud Platform
Google Cloud Profiler
New Relic
Integrations
CData Connect
DataBuck
Google Cloud Bigtable
Google Cloud Composer
Google Cloud Dataplex
Google Cloud Datastream
Google Cloud IoT Core
Google Cloud Platform
Google Cloud Profiler
New Relic
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Founded
1998
Country
United States
Website
cloud.google.com/dataflow
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/cloud/streaming-analytics
Product Features
Streaming Analytics
Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards
Product Features
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports
Streaming Analytics
Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards