Here’s the difference between Looker and Google Cloud Dataflow. The comparison is based on pricing, deployment, business model, and other important factors.
Looker is a data integration and visualization solutions, provider. It offers cloud-based data integration and visualization platform to enterprises. It enables businesses to access data that is connected from multiple different sources. This includes cloud applications such as Salesforce, Zendesk, business planning applications, and web analytics tools. It also provides a custom visualization library and pre-modeled external datasets such as weather and demographics data. It provides solutions to industries including eCommerce, media, healthcare, and gaming among others. Some of its notable clients include Buzzfeed, Intercom, Twilio, and Hubspot, etc.
Google Cloud Dataflow is a cloud-based data processing service for both batch and real-time data streaming applications. It enables developers to set up processing pipelines for integrating, preparing and analyzing large data sets, such as those found in Web analytics or big data analytics applications. The Cloud Dataflow software expands on earlier Google parallel processing projects, including MapReduce, which originated at the company. Cloud Dataflow is designed to bring to entire analytics pipelines the style of fast parallel execution that MapReduce brought to a single type of computational sort for batch processing jobs.
Overview | ||
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Categories | Business Intelligence (BI) | Data Streaming |
Stage | Late Stage | Late Stage |
Target Segment | Enterprise, Mid size | Enterprise, Mid size |
Deployment | SaaSOn Prem | SaaS |
Business Model | Commercial | Commercial |
Pricing | Contact Sales | Freemium |
Location | California, US | US |
Companies using it | ||
Contact info |