Difference Between Hadoop and Splunk

Hadoop is a framework for handling "Big Data" in simpler terms. Hadoop processes massive amounts of data using a distributed file system and the map-reduce technique.

Splunk is a tool for monitoring. It provides a platform for log analytics, analyses log data, and visualizes the results. Splunk provides web-based access to tools for indexing, searching, monitoring, and analyzing machine data.

In this article, we will explore Hadoop vs. Splunk in depth.

What is Hadoop?

The Apache Hadoop software library is a platform that enables the distributed processing of massive data volumes using basic programming paradigms across clusters of machines. Hadoop is a framework for handling "Big Data" in simple terms. It is scalable from a single server to thousands of devices, each providing local computing and storage. Hadoop is an open-source program. Hadoop's storage component is the Hadoop Distributed File System (HDFS), while its processing component is a Map-Reduce programming approach. Hadoop divides files into big pieces and distributes them across a cluster of machines. It then transfers packed code onto nodes for parallel data processing. Doug Cutting and Mike Cafarella built Hadoop in 2005.

Features:

• Hadoop is Open Source.
• The Hadoop cluster is Extremely Scalable.
• Hadoop enables Fault Tolerance.
• Hadoop offers high Availability.

Advantages:

Hadoop is an open-source system, meaning its source code is publicly accessible. We may edit source code as per our business needs. Even proprietary Hadoop implementations, such as Cloudera and Horton works, are available.

Hadoop is scalable and operates on a cluster of machines. Hadoop is very scalable. We may extend the size of our cluster as needed by adding more nodes with no downtime.

Hadoop is schema-independent and can process a variety of data formats. It is versatile enough to hold numerous data types and can operate on both organized and unstructured data (unstructured).

Disadvantages:

• Hadoop can be complex to set up and maintain, requiring specialized expertise and resources.
• It can be slow for certain types of data processing, especially when dealing with small amounts of data or real-time analytics.
• Hadoop is not suitable for low-latency applications, such as online transaction processing or interactive queries.
• The cost of storing and processing large amounts of data on a Hadoop cluster can be prohibitively expensive.

What is Splunk?

Splunk is a web-based application primarily used for finding, monitoring, and analyzing machine-generated Big Data. Splunk captures, indexes, and correlates real-time data in a searchable container, from which graphs, reports, alerts, dashboards, and visualizations may be generated. Splunk is a tool for monitoring. It seeks to make machine-generated data accessible throughout an enterprise and can analyze data trends, develop metrics, diagnose issues, and provide business insight. Splunk is used for application administration, security, compliance, and business and web analytics. Michael Baum, Rob Das, and Erik Swan co-founded Splunk in 2003.

Features:

• Boost Development and Testing
• Enables the development of Real-time Data Applications
• Generate ROI quicker
• Agile reporting and analytics with Real-time architecture
• Provides search, analysis, and visualization tools to enable all sorts of users.

Advantages:

• Splunk offers real-time monitoring, event management and alerting, and insight into the health of physical and virtual IT infrastructure.
• Splunk also offers application, business, and IT service monitoring.

Disadvantages:

• Pricing increases somewhat for huge data quantities. Optimization of search results is more art than science.
• Compared to the tableau, the dashboard seems quite harsh. Continuous efforts are being made to replace it with open-source alternatives.
• Splunk can be expensive, especially for large organizations with complex data analytics needs.
• Splunk's reliance on a proprietary search language and data format can limit its interoperability with other systems and tools.

Hadoop vs. Splunk

Conclusion

Finally, we have come to the end of this detailed comparison between hadoop vs. splunk. We hope you like this tutorial. We have started with a brief introduction to hadoop vs. splunk. We also explored the advantages, disadvantages, and features of hadoop vs. splunk. Finally, we have compared hadoop vs. splunk.

Please let us know in the comment box if you have difficulty following along. Happy learning!

Related Questions

1. Can you combine Splunk with Hadoop?

Splunk Hadoop Connect enables dependable interaction between Splunk and Hadoop. It provides three fundamental capabilities: Export, Exploration, and Import. Export — Enables the transfer of Splunk data to Hadoop. Export is a method for sending unprocessed or raw events to Hadoop reliably and predictably.

2. What kind of tool is Splunk?

Splunk is a software platform for searching, analyzing, and visualizing machine-generated data collected from your IT infrastructure and company's websites, apps, sensors, and other components.

3. Is Splunk an ETL tool?

Traditional extract, transform, and load (ETL) methods need all data to be formatted before gaining insights, slows down the analytics process. But Splunk Enterprise is different. It is an ELT (extract-load-transform) platform.

4. Is coding required for Splunk?

You need no coding knowledge. The only need for beginning this lesson is a computer capable of running Splunk Enterprise. Whether you want to create applications for Splunk Cloud Platform or Splunk Enterprise, your development environment requires a local installation of Splunk Enterprise.