Compare Datazoom And Popular Video Analytics Tools

Although Datazoom is the industry’s first Video Data Platform, there are many tools available which offer premade insights into the viewer experience. But their offerings vary greatly from the flexible, scalable, reliable video data platform offered by Datazoom. The table below shows you how datazoom compares with popular video analytics tools.


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  • Datazoom DaaS Platform Versus Video Analytics Tools

See How Datazoom Compares With Popular Video Analytics Tools

Data First, Analytics Second.

The Datazoom Video Data Platform is more than just an analytics tool. Don’t waste effort on implementing an analytics tool when what you need is a platform to manage, govern, and deliver your data.  Learn how Datazoom stacks up against the competition in the table below and click on a competitor’s logo to learn more about how Datazoom compares.

Features and Capabilities
Features and Capabilities
Change Data Heartbeat Frequency
Change Collected Data Points Anytime
Collector Ecosystem
Configurable Analytics Connectors (No API Integration Required)
Exposes API to Export Metrics
1-To-Many Real-Time Data Routing Via Connectors
Adjust Connector Sample Rate Anytime
Core Video Player Event-Level Data Collection And Access
CDN Log Data Collection
Unlimited, Self-Configured, Custom Data Collection
Real-time Data Enrichment
Roadmap To End-to-End Data Collection
Reliability and Data Governance
Rigorous, Event-Level Data Lag Monitoring (With SLA)
Data: Validation, De-Duplication, And Retries
Integration And Data Quality Testing
Privacy Compliance
Pricing Structure
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Here Are Some Of The Features That Differentiate The Datazoom Data-as-a-Service (DaaS) Platform From the Competition

More Than Just Video Analytics

When you choose the Datazoom DaaS Platform over run-of-the-mill video analytics tools,  you get a suite of powerful tools and features which solve critical challenges to providing a high QoE for viewers, fast and more effective operational support, and even maximizing revenue.


Collectors represent established integrations with popular data end-points such as video players, like JW Player, and CDNs, such as Akamai and Lumen. You can pick from these collectors when building your datapipes.


Connectors represent established integrations with popular storage providers, such as AWS and Google, and visualization tools, such as Datadog and Splunk. You can pick from these connectors when building your datapipes.


The frequency at which you need data from end-points may be different. Some you need in near real-time, others can be delivered later. With Datazoom you can set a collection frequency per data point.


With Datazoom, you can add datapoints to existing JSON streams such as combining ad CPM with ad-event data. This can reduce the amount of post-processing required, such as table matching, and speed-up monitoring and analysis.


Analyzing large datasets, such as CDN logs, can be costly in terms of both computing resources and the time it takes to process. This can significantly increase the time it takes to resolve an issue. With Datazoom, you can specify just a subset of a data source.


Data consistency is a big challenge. If data sources utilize different names for the same value, it can be difficult to relate them. Datazoom’s CDN Dictionary and Video Player Data Dictionary help to automatically standardize data values.


With Datazoom, you can change variable names, types, and other modifications to ensure that the data which reaches you is already compatible with your visualization tools and calculations.

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