Apache Storm

Analyzing large volumes of data with Apache Storm

Conclusions

Apache Storm provides a big data solution for companies and meets even the highest demands. Although commissioning a big data cluster is quite easy to deal with, creating your own topologies means delving deeper into the subject. Storm, its interfaces, and API may be documented in great detail, but it is still missing a convenient (visual) tool for developing topologies.

Alternative Open Source Big Data Systems

There's no doubt that big data problems will be with us for many years, and probably even decades, because companies need solutions for processing the rapidly growing amounts of data. Besides Hadoop and Storm, several other interesting solutions are available, especially in the open source area.

Couchbase [3] is a NoSQL database, but it also allows a big data environment to be created easily by integrating MapReduce and collaborating with Hadoop. The high-performance database system is suitable for processing large amounts of data. Couchbase is available in Community and Enterprise versions.

Talend Open Studio for Big Data [4] promises the use of big data without having to write your own code. The environment provides various connectors for all relevant data sources. The big data solution includes, among others, functions such as standardization, parsing, data enrichment, matching, survivorship, and the continuous monitoring of data quality.

Lumify [5] was developed specifically for data analysis and visualization. The tool is used in particular for the aggregation, organization, and extraction of new views and insights. A few other projects under the umbrella of the Apache Foundation are devoted to the topic of big data. Apache Drill [6], for example, is a distributed system for interactive analysis of huge volumes of data. Spark [7] even claims to perform 10 to 100 times faster than Hadoop.

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