Top 6 Trending Big Data Analytics Tools for 2024

In today’s data-driven world, organizations across industries gather vast amounts of information. Effectively analyzing this data is crucial for making informed decisions and refining strategies. This massive dataset, known as big data, includes both structured and unstructured information. To handle this variety of data, organizations rely on advanced analytics tools. Here are six of the most popular and effective big data tools currently in use:

Presto
Developed initially by Facebook, Presto is an SQL-based query engine that became open source in 2013. Major companies like Netflix, Airbnb, and Teradata leverage Presto’s capabilities to query massive datasets efficiently. It can process petabytes of information and quickly retrieve data from various sources, enabling comprehensive analytics across multiple systems.

Apache Hadoop
One of the most widely used big data tools, Hadoop specializes in processing vast amounts of data through a distributed framework. Built with Java, it is open source and excels in environments such as banking and finance, where large-scale data analysis is essential. Hadoop utilizes a networked system of computers to store and analyze data locally.

PolyBase
PolyBase allows seamless analysis of both relational and non-relational data, making it ideal for querying data stored in Hadoop, Azure Data Lake, or Blob Storage. Its advantages include scalable performance, flexible storage options, and enterprise-grade security features, enabling efficient big data analysis in mixed data environments.

Hive
Operating on top of Hadoop, Hive facilitates managing distributed data within Hadoop clusters. Using HiveQL, a language similar to SQL, organizations can perform data mining and query big datasets effectively, making it a valuable tool for data analysis and mining initiatives.

NoSQL
Most big data involves unstructured data that traditional databases struggle to handle. NoSQL databases are designed to efficiently store and query large volumes of unstructured data. With several open source options available, organizations can customize NoSQL solutions to meet their specific analytics needs.

Big Data in Excel
By integrating Hadoop with Excel 2013, users can connect directly to big data sources for analysis. Using Hortonworks’ Enterprise Apache Hadoop platform, Excel’s Power View feature helps summarize and explore large datasets seamlessly, allowing users to derive insights without specialized skills.