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API to write data to Cassandra:

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  • In contrast, using the REST API allows the Java piece to be changed or replaced without having to re-create your input process.
  • Another advantage to using an API for writing is that you can queue input requests if there is a surge in usage or incoming requests to handle them as quickly as possible without message loss due to maximum connection limits or other networking issues.
  • NoSQL stores are now an mandatory part of any framework, the SMACK stack (Spark, Mesos, Akka, Cassandra and Kafka) is becoming well popular.
  • Its demonstrated scalability and its high write throughput create it the perfect partner to manage the flood of time series, IOT and industrial scale streams or financial data.
  • This made Apache Cassandra an clear choice as a Connect API in Kafka sink.
api to write data to cassandra
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Cassandra database software

  • Apache Cassandra is a simple and open-source provides NoSQL DBMS build to handle huge volume of data against more fabric servers.It providing high availability with no single point of failure.
  • The performance of Cassandra place a high value. In 2012, University of Toronto researchers studying NoSQL systems resulted that “Scalability defined there is a clear winner throughout our experiments.Cassandra achieves the largest throughput for the large number of nodes in all experiments” although “it determine at the price of high write and read latencies.”
cap theorem

Main features:

Decentralized

  • Cluster contain every node has the same role.
  • There is no single point of failure.
  • To provides data across the cluster so every node have various data, but there is no master as every node can service if any request.

Supports replication and multi data center replication:

  • Replication strategies are configurable.
  • Cassandra is built as a distributed system, for deployment of maximum numbers of nodes across many data centers.
  • Key features of Cassandra’s distributed architecture are specifically change for multiple-data center deployment, for redundancy, for fail over and disaster recovery.

Scalability:

  • As new machines are added read and write throughput both increase linearly, with the achieve of no halt or interrupt to applications.

Fault-tolerant

  • Data is automatically replicated to many nodes for fault-tolerance. Replication across multiple data centers is maintained. Failed nodes can be changed with no downtime.
cassandra

Tunable consistency

  • Writes and reads gives a adjustable level of consistency, all the way from “writes never fail” to “block for all replicas to be readable”, with the quorum level in the middle.

MapReduce support

  • Cassandra has Hadoop integration, with MapReduce support.
  • There is support also for Apache Pig and Apache Hive.
apache cassandra
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