QDS offers Cascading as a service for Java programmers and users who want to future-proof their querying capabilities to accommodate massive amounts of data and large cluster sizes - all built into their Java applications. Leveraging Cascading greatly reduces the amount of setup, component familiarity, and granularity of control requirements in order to simplify Big Data projects. On QDS, Cascading takes advantages of extensive optimizations of Hadoop, including autoscaling and cluster life cycle management - further simplifying the administration of Cascading jobs.
Like all big data solutions supported by QDS, clusters scale up and down automatically during query execution. And you don't have to worry about starting or stopping Spark clusters... SEE MORE
Like all big data solutions supported by QDS, clusters scale up and down automatically during query execution. And you don't have to worry about starting or stopping Spark clusters. QDS does all the heavy lifting for you.
QDS makes it easy to debug both active and historical jobs with a Spark Application UI. Results and logs are always available even without active running clusters.
QDS lets you automatically incorporate Amazon spot instances that can be up to 90% less than the cost of on-demand instances.
With QDS' pay-per-use pricing model, you'll only pay for what you actually use by compute hour.
QDS gives you user interface options to match your use case. The Spark Notebook and a web-based UI are suited for interactive analysis, and the SDK'ss and the REST API are ideal for programmatic access.
QDS supports Amazon VPC, a service that extends your private network into the cloud. Amazon VPC provides fine-grained access control both to and from Amazon EC2... SEE MORE
QDS supports Amazon VPC, a service that extends your private network into the cloud. Amazon VPC provides fine-grained access control both to and from Amazon EC2 instances in your virtual network. Plus, you can launch dedicated instances within a VPC on single-tenant hardware.
Cascading simplifies the ability to extract, transform and load large datasets in Hadoop rather than writing complex MapReduce programs. Programmers can easily execute batch ETL jobs to transform unstructured and semi-structured data into usable schema-based data within their Java applications. Cascading can also leverage the QDS Hive Metastore which makes metadata for tables and partitions easily accessible.
Teams who want to quickly build Big Data analytics into their applications are best served with Cascading as a Service on QDS. Additionally, diverse teams can leverage the common metadata offered on all QDS Data Engines to work in conjunction with other teams using other tools. Some data science users may prefer to use Hive or Spark for analysis. With QDS, these teams do not have to work separately, but can easily leverage each other's work through their interface of choice.
Qubole offers 2 weeks of QDS usage for free to explore Cascading and other data engines. Users simply need to authenticate with SSO or enter their AWS credentials to begin interacting with their data in their own cloud environment.Try Cascading Today!