Building powerful and effective Big Data workloads
Enterprise solutions for building scalable data deployment and management strategy.
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Apache Spark Development Solutions
Apache Spark is a high-performing large-scale analytics and data processing engine that offers high batch and interactive processing performance.
Streamlined Operations
Apache spark streamlines data processing objectives with in-memory computing capabilities and super-fast queries.
Empower Interactive analytics
Spark-based real-time predictive analytics solutions for enterprises to gain faster and more practical business insights.
Run workloads Faster
With managed workloads, organizations can work on reducing costs and maximizing workload efficiency.
Empowering Apache Spark as a Service
Apache Spark is a fast cluster computing platform developed for performing computations and stream processing activities. Understand how it assists in building and processing data applications.
Pricing Plan
Apache Spark Implementation Solutions
Monitoring Solutions
24x7 monitoring and support solutions for promoting efficient and faster workload performance.
Performance monitoring capabilities
Apache Spark comes with a shared memory pool for execution and caching, further empowering self-managing and optimization abilities.
Apache Spark engine is present in the operational database, which means there is no need for extracting, transforming, and loading into a new environment.
Resilient Distributed Datasets driven solutions for extending Immutability, Fault Tolerance, and partitioning capabilities.
Apache Spark has an advanced DAG execution engine that supports cyclic data flow and in-memory computing, running application to run up to 100x faster.
Large-scale Data processing with Spark
Facilitate and build completely managed parallel and integrated operations with Dataproc.
Deploy Spark Clusters on AWS
Empower scalable and reliable applications with optimized query execution and implementation solutions.
Azure HDInsight Solutions
Enterprises can utilize HD insight abilities for easy administration and configuration of Spark clusters.
Related Data Processing Insights
Running Apache Spark applications on AWS
Running Apache Spark applications on AWS
What are the features of Apache Zeppelin?
What are the features of Apache Zeppelin?
Building Real Time Streaming Application with Apache Spark
Building Real Time Streaming Application with Apache Spark
Apache Hadoop
Real-Time Streaming Architecture
Apache Flink
Apache Kafka
Apache Hadoop
Apache Hadoop is a framework that allows storing large Data in distributed mode and allows for the distributed processing on that large datasets. It designs in such a way that scales from a single server to thousands of servers.
Real-Time Streaming Architecture
Apache Spark Streaming is the tool to specify the time-based window to stream data from our message queue. So it does not process every message individually.
Apache Flink is useful in efficient disk spilling, network transfers, and reduction of Garbage Collection.
Apache Kafka
Apache Kafka is a public subscribe scalable messaging and fault-tolerant system that helps us to establish distributed applications.
Leverage Continuous Intelligence Capabilities
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Automate actions to uncover the unknown
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Transform processes to move at market speed
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Accelerate business outcome with more accurate predictions in real time
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