Big Data

Big Data services Details
Process vast amount of data and get insight
We utilize the power of the Apache Spark to get the data processed.
Apache Spark Speed
Apache Spark Speed
Apache Spark is fast, faster than Hadoop

Morden world generates petabytes of data and that too may not fully structured. Trying to get a deeper insight into those data is difficult and cumbersome. With the right set of tools, we can help you to get those much-needed insights and that too with greater resolution.

Apache Spark Stack
Apache Spark Stack
Apache Spark Stack
Spark SQL
Spark SQL is built on top of Shark used for interactive data processing. This customized query language provides functionalities for handling large distributed data.
Spark Streaming
Spark Streaming is a high-level extension of core Spark API primarily aimed at streaming large data, with scalable and fault tolerance in mind. Data can be consumed from various sources including Kafka, Flume, Kinesis, or TCP sockets.
Apache Spark MLlib is the Apache Spark machine learning library consisting of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, and underlying optimization primitives.
GraphX is Apache Spark's API for graphs and graph-parallel computation. It extends the Spark RDD by introducing a new Graph abstraction: a directed multigraph with properties attached to each vertex and edge.
Apache Spark Stack
Apache Spark Technology
Major technologies involved in Apache Spark
Apache Hadoop is a collection of open-source software utilities that facilitate using a network of many computers to solve problems involving massive amounts of data and computation.
Apache Cassandra is a free and open-source, distributed, wide column store, NoSQL database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure.
Apache HBase
HBase is an open-source non-relational distributed database modeled after Google's Bigtable and written in Java. It is developed as part of the Apache Software Foundation's Apache Hadoop project and runs on top of HDFS or Alluxio, providing Bigtable-like capabilities for Hadoop.
Mesos is built using the same principles as the Linux kernel, only at a different level of abstraction. The Mesos kernel runs on every machine and provides applications (e.g., Hadoop, Spark, Kafka, Elasticsearch) with APIs for resource management and scheduling across the entire datacenter and cloud environments.
Kubernetes is an open-source container-orchestration system for automating application deployment, scaling, and management. It was originally designed by Google and is now maintained by the Cloud Native Computing Foundation.