Earlier this week, Apache Software Foundation unveiled its latest Top Level Project (TLP), Flink.

Flink is just one of the many data processing tools that have emerged since the Java-based distributed computing platform Hadoop has increased adoption in the enterprise space.

Flink is much like Hadoop in that it can look into big data sets that are simply too large to fit into traditional data warehouses or relational databases. It can also work with unstructured data such as event logs.

What sets Flink apart from Hadoop is that it can analyze streaming data and leverage in-memory processing to enhance processing speed.

Flink is ideal for organizations that are looking for faster performance and a replacement for Hadoop, according to Kostas Tzoumas, CEO of Data Artisans, one a spinoff company that will commercialize Flink.

The application programming interface (API) for Flink is also easier to use that programming for Hadoop’s MapReduce, especially when employed for large projects, he said.

A recent article in, however, said that Flink may face stiff competition from Hadoop and Spark, another data processing platform that share some traits with Flink.

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