Apache Hadoop as a Service

 

Hadoop as a Service, as offered by Qubole Data Service (QDS) is a cloud computing solution that makes medium and large-scale data processing accessible, easy, fast and inexpensive. This is achieved by eliminating the operational challenges of running Hadoop, so you can focus on business growth.

 

Why Hadoop in the Cloud?

With its unlimited scale and on-demand access to compute and storage capacity, cloud computing is the perfect match for big data processing. Qubole's Hadoop as a Service offering has several advantages over on-premise solutions.

On-Demand Elastic Cluster

 

Unlike static, on-premise clusters, Hadoop clusters in the cloud scale up or down depending on data processing requirements. Nodes are automatically added to or removed from clusters depending on data size to improve performance.

 

Integrated Big Data Software

 

Hadoop as a Service includes full integration with the Hadoop ecosystem, including MapReduce, Hive, Pig, Oozie, Sqoop, Spark and Presto. Connectors for data integration and creating data pipelines provide a complete... SEE MORE

Integrated Big Data Software

 

Hadoop as a Service includes full integration with the Hadoop ecosystem, including MapReduce, Hive, Pig, Oozie, Sqoop, Spark and Presto. Connectors for data integration and creating data pipelines provide a complete solution that works with your current pipeline.

 

Simplified Cluster Management

 

Qubole Data Service offers a fully managed Hadoop-based cluster, eliminating the need for extra time and resources devoted to managing nodes, setting up clusters and scaling infrastructure.

 

Lower Costs

 

Hadoop in the Cloud requires no upfront investment in on-site hardware or IT support. Spot instant pricing reduces costs up to 90% compared to on-demand instances. Pay for space only when you use it with auto-scaling clusters.

 

Why Hadoop?

The emergence of Hadoop has changed the data landscape. With Hadoop, you can gain new or improved business insights from structured, unstructured and semi-structured data sources. In addition, large volumes of data which were previously too expensive to store or siloed among departments can be gathered and analysed in one place at an affordable price.

“We are growing very fast as a startup and needed a way accelerate our time to value for Hadoop,” explains Mickey Alon, Insightera?s CEO and Co-founder. “We wanted to focus more on data processing and turning insights into actionable results, and less on the operational side of Hadoop and Amazon S3 for tackling our Big Data integration challenges.”

Mickey Alon, Insightera's CEO and Co-founder

 

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