Top 8 Big Data Platform Tools Free 2023 (Update)

Big Data Platform Tools – If you are interested in using big data, don’t hesitate to contact Ivosights. We will be happy to explain more about our services and how we can help your business produce a more informative and useful annual report.

With our big data services, you will get access to accurate and detailed data about your business performance. We will analyze the data and present the results in an easy-to-understand report. The report will help you identify positive and negative trends in your business, as well as provide useful recommendations for improving future performance.

What Are Big Data Platform Tools ?

Big data analysis requires powerful computing technology and sophisticated data analysis techniques to deal with the volume, speed & complexity of data.
Big data is a collection of data that is too large and complex to be handled with traditional data analysis tools.

Big data usually includes data that comes from various sources such as business transactions, social media interactions, digital sensors, and geospatial data. This data can be structured or unstructured data, and can contain text, images, sound, or numeric data.

Data analysis of big data requires powerful computerized technologies and sophisticated data analysis techniques to deal with the volume, speed and complexity of data. By using the right data analysis tools, your company can uncover useful patterns and insights from big data.

For example, a company can use customer data to determine customer preferences and shopping habits, thereby optimizing promotions and sales. Alternatively, a business can use geospatial data to determine the right location to open a new branch, or to determine customer travel patterns.

Big data analysis can also be used to identify risks and opportunities, improve operational efficiency, and improve service quality. Thus, big data can be a useful source of information for companies, and help you make better decisions and improve business performance.

Top 6 Big Data Platform Tools Free 2023 (Update)

Big Data is a specific term used for data that exceeds the processing capacity of conventional databases because it is too large, moves too fast, and does not fit the structural capabilities of traditional database architectures.

So we have to carry out a process with an integrated system capable of handling Big Data called Big Data Analytics. While data science is the study of raw data and unstructured data that processes it through expertise.

Use skills such as statistics and mathematics, programming or IT, data processing, data analysis and broad knowledge of various fields.


To assist in dealing with this, we need supporting tools, both tools for big data and data science. Companies regard a company’s data as new oil, because companies face how to mine valuable oil to make a profit?

Think of it as data in lakes, pipelines, and warehouses to capture business and enterprise market gaps as channels to help answer calls and grow the business going forward.

That’s why Analytics Insight collects the top big data tools of 2023. Here are the best Big Data apps for business and data analysis:

1. MongoDB

MongoDB, the platform founded by Kevin Ryan, Eliot Horowitz, and Dwight Meriman is one of the next generation databases that helps in business change by using the open NoSQL concept and trusted.


MongoDB is well-known among developers because it has an advantage in its strength which has flexibility compared to the Apache Hadoop program which is written in C++ and data storage does not use tables but uses structured documents such as JSON.

In addition, MongoDB features high performance, automatic scaling, and high availability. MongoDB makes use of Javascript to operate aggregation, indexing, CRUD and various other database operations.

2. Apache Hadoop

Apache Hadoop, appeared in 2005 which is open software that is used to store data and run applications in a cluster or one unit.


Hadoop can connect various computers to work together and be connected to each other in their use. Hadoop can store and process large data in a distributed manner using the MapReduce programming model.

In addition, storage can also be parallel in clusters with hundreds of servers because it consists of thousands of computers. Users can also increase the cluster size by adding new nodes as needed without downtime.

3. Pentaho

Pentaho is a comprehensive solution that supports the entire big data cycle in the enterprise. Big data analytics at Pentaho offers various kinds of analytical solutions in accessing data and integrate into visualization and predictive analytics.


In Pentaho, we can see various information from the data that is presented in the form of an interactive report.

Pentaho has several functions such as analyzing data, creating scheduled or on-demand reports in various formats, creating Pentaho Dashboards, and conducting data mining.

4. RapidMiner

RapidMiner is a software platform developed in 2001 for big data science teams that brings together data preparation, machine learning, and predictive modeling.

In addition, RapidMiner is also a free open software for data and text mining as well as the most powerful and intuitive graphical interface for the design of the analysis process.


It is used for commercial and business, research, training, education, rapid prototyping, and application development that supports all steps of the learning process including data preparation, visualization results, model validation, and optimization.

5. Cassandra

Apache Cassandra is an open source product for managing databases distributed by Apache that is scalable and designed to manage very large data spread across multiple servers.

Cassandra is a leading NoSQL that is suitable for hybrid and multi-cloud environments. In addition, access performance becomes faster so that NoSQL.

It’s getting more and more popular lately. Several large companies have used Cassandra, such as Facebook, IBM, DIgg, Reddit, Apple, Twitter, and others.

You need a big data tool that you will provide scalability and high availability and excellent performance?

Then, Apache Cassandra is the best choice for you. This tool is a free, open source NoSQL distributed database management system.

For its distributed infrastructure, Cassandra can handle high volumes of unstructured data across commodity servers.

6. Big Data Platform Tools Quble

Quoble is a cloud-native data platform that develops machine learning models at enterprise scale. The vision of this tool is to focus on data activation.

This makes it possible to process all kinds of data sets to extract insights and build artificial intelligence based applications.

7. Big Data Platform Tools Hadoop

Apache Hadoop is one of the most prominent tools. This open source framework enables reliable distributed processing of large amounts of data in datasets across clusters of computers.

Basically, it is designed to upgrade a single server to multiple servers. It can identify and handle failures at the application layer. Several organizations use Hadoop for their research and production purposes.

8. ApacheSpark

Apache Spark is a super-fast integrated analysis engine (software) for processing data on a large scale, includes Big Data and machine learning.

In addition, Apache Spark has a different algorithm than Map/Reduce, but can run on top of Hadoop via YARN.

In more detail, Apache Spark can be defined as an engine for processing large-scale data in-memory, complete with an elegant and expressive development API.


This is to make it easier for data workers to execute jobs that require fast repeated access to the data being processed. Like streaming, machine learning, and SQL, efficiently.

So that the core of Spark is a distributed execution engine, and Java, Scala and Python APIs are provided as platforms for developing distributed ETL (Extract, Transform, Load) applications.

Then, additional software libraries, which build on top of the core, facilitate various types of work related to streaming, SQL, and machine learning.

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