Analytics Services


Run and Scale Hadoop, Spark and HBase On-Prem to Easily and Effectively Process Big Datasets

Chorus Analytics Services

Chorus offers managed Hadoop, Spark and HBase services that ensure simple and timely solutions for on-prem big data initiatives , eliminating the need to migrate vast amounts of data to the cloud. Chorus’ Big Data Services, compatible with AWS EMR (including APIs), integrates with Symphony’s storage, compute, and monitoring services to offer cluster provisioning and monitoring across on-prem EC2-compatible instances and cost effectively scale workloads. By leveraging existing on-prem resources, enterprises can protect their data assets and deliver an easy-to-use multi-tenant and secure solution, that is easy to deploy and manage over time.

Watch how you can easily launch and manage Hadoop clusters

Reduce Time to Market

Empower developers with self-service Hadoop deployment, including provisioning, cluster setup and configuration

Optimized Costs

By running big data projects on-prem, the cost structure remains predictable and stable. Leveraging commodity built-in storage or external storage appliance offers optimal flexibility for each project with its unique requirements and attributes

Run Analysis as Close as Possible to Data

Eliminate the need to migrated data to public cloud environments, by effectively leveraging on-prem infrastructure that is fully compatible with AWS services and APIs


Minimize cluster monitoring and management efforts. Chorus monitors cluster activities, failed tasks and performance; unhealthy instances are taken out of rotation, and will be reactivated when possible

Speed Up Development of Cloud-Native Applications

It’s easy and essentially effortless to deliver turnkey cloud-native building blocks to support modern applications on-prem.

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Chorus Analytics


Stratoscale Chorus


On-demand Cluster Provisioning

Automatically create, manage and monitor Hadoop, Spark and HBase clusters.

Highly Available Underlying Storage

Leverage Stratoscale’s abstracted, persistent block storage and object storage and transparently use storage pools from different backends.

Optimal Flexibility

Use big data clusters for a wide variety of use cases and applications while ensuring full control of the cluster. Each cluster is customizable for according to requirements.


Clusters fully separated to offer a true multi-tenant service.

AWS EMR-Compatible APIs

Offer standard AWS APIs for application integration.

Use Cases

Edge Computing

In some use cases, sending data to the cloud for processing has become ineffective, from performance and cost perspectives, and at times no longer possible. Leverage Stratoscale’s on-prem infrastructure and cloud-grade big data services to support data-heavy cloud-native applications to ensure effective dataset processing.

Internet of Things

The number of connected devices continues to grow in unprecedented pace and spans across a very wide variety of industries: industrials, medical, automotive, transportation, etc. Chorus’ on-prem Big Data Services support processing of millions of events per second and provide real-time big data analytics without compromising on the simplicity and flexibility of the cloud.

Data Science and Machine Learning

Accelerate intelligence and data-driven business initiatives and provide applications with strong and effective analysis tools. The self-service consumption model and AWS-compatible APIs offer developers a simple single-click access to big data tools and ensure a long-term flexibility in running cloud-native applications on-prem or in the cloud.

A True Hybrid Model for Data Analysis

When it comes to data, enterprises encounter various considerations (data gravity, performance, security, networking, etc.) in where to develop and deploy applications. These considerations may change during the application lifecycle, making flexibility a key element for developers and IT organizations. Stratoscale’s AWS-compatible environment offers enterprise the ability to run cloud-native data analysis projects on-prem, while maintaining full control, visibility and cost efficiency, as well as burst to the cloud when needed without the need to re-write applications or make any adjustments.

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Easily process and scale big datasets on-prem

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