5 Streaming Analytics Platforms For All Real-time Applications

Through Streaming analytics, real-time information can be gathered and analyzed from and on the cloud. The information is captured by devices and sensors that are connected to the Internet, as part of the Internet of Things disruption.

Streaming analytics solutions allow organizations to build real-time solutions using IoT and extract information from them later using Big Data, or to churn them first-hand using real-time processing. The power of streaming analytics is such that it allows for the streaming of millions of events in a second and thus allows enterprises to build mission-critical applications that require the performance to be quick and efficient.

Real-time streaming analytics can, for example, present to you the statistics if your latest online ad campaign is working as expected, or if it needs some tweaking to work better. Such applications want to always stay upgraded for performance benefits.

Here are the top platforms being used all over the world for Streaming analytics solutions:

Flink is an open-source platform that handles distributed stream and batch data processing. At its core is a streaming data engine that provides for data distribution, fault tolerance, and communication, for undertaking distributed computations over the data streams. In the last year, the Apache Flink community saw three major version releases for the platform and the community event Flink Forward in San Francisco. Apache Flink’s open-source contributors on Github have increased from 258 in December 2016 to 352 in December 2017. Apache Flink contains several APIs to enable creating applications that use the Flink engine. Some of the most popular APIs on the platform are- DataStream API for unbounded streams, DataSet API for static data embedded in Python, Java, and Scala, and the Table API with a SQL-like language.

Apache Spark is used to build scalable and fault-tolerant streaming applications. With Spark Streaming, you get to use Apache Spark’s language-integrated API which lets you write streaming jobs in the similar way as you write batch jobs.