Big Data Architecture: An Overview

Big Data Architecture: An Overview

Big data is a term that refers to complex, large and disparate data sets that are too difficult to process using traditional data processing systems. These data sets not only involve structured but also semi and unstructured data from various sources such as social media platforms, mobile devices, servers, and many others. By processing and analyzing these data sets, organizations can generate essential insights into their operations, clients, and partners that can lead to optimized decision making, enhanced productivity, and better customer experiences.

However, the nature and size of Big Data require specialized processing tools and architectural frameworks to extract valuable insights from it. Big Data architecture refers to the systematic approach of organizing and managing large and complex data sets that enables meaningful analyses and business insights.

This article will provide an overview of Big Data Architecture, its layers, tools, and patterns. We will also discuss some examples of Big Data architectures and their applications.

Big Data Architecture Layers

A big Data architecture consists of several interconnected layers that are designed to support the processing, management, and analysis of large and complex data sets. The layers are:

Foundation Layer

The foundation layer is the base layer of Big Data architecture where all the data is stored. This layer involves the collection, storage, and processing of large and messy data sets from various sources such as sensors, social media platforms, mobile devices, and IoT devices. This layer includes various technologies such as Hadoop Distributed File System, NoSQL databases, and others. The primary aim of this layer is to process large volumes of data quickly and efficiently. The data stored in this layer is raw and unstructured, making it difficult to analyze and interpret.

Ingestion Layer

The ingestion layer is responsible for data acquisition and the integration of various data sources into the big data architecture. This layer involves technology such as Apache Kafka, Nifi, the ETL process, and others. This layer filters the incoming data from different sources and ensures that the data is efficiently stored in the storage layer or processed by the analysis layer.

Integration Layer

The integration layer is responsible for adding structure and consistency to the raw data stored in the foundation layer. This layer involves technologies such as data warehousing and data marts where the formatted data is stored, integrated, and managed. This layer also includes data validation, data cleaning, and data transformation processes.

Analysis Layer

The analysis layer consists of technologies designed to query, analyze, and extract useful insights from the integrated and formatted data in the foundation layer. This layer includes technologies such as data mining, business intelligence, machine learning, and others. The primary aim of this layer is to provide useful insights and actionable data to business users.

Presentation Layer

The presentation layer involves the tools and technologies used to present the analyzed data to the end-users in the form of reports, dashboards, and visualizations. This layer includes technologies such as Tableau, Power BI, and QlikView.

Big Data Architecture Tools

The following is the list of widely used tools that can be used to build big data architectures:

  1. Hadoop
  2. Hadoop is a popular open-source big data platform for distributed storage and processing of large data sets across clusters of computers. It provides a framework that allows users to distribute and process large data sets that are too large to be handled by traditional data processing systems. Hadoop ecosystem includes Pig, Hive, Spark, and others.

  3. Apache Spark
  4. Apache Spark is an open-source cluster-computing framework designed for large-scale data processing and analytics. It provides an interface for programming entire clusters using Scala, Python, and R languages, making it easy to write and deploy large-scale applications.

  5. NoSQL Databases
  6. NoSQL databases are databases designed to handle large volumes of unstructured and semi-structured data from various sources such as Social media, IoT devices, and others. They are designed to be scalable and highly available. Examples of NoSQL databases are MongoDb, Cassandra, and HBase.

  7. Apache Storm
  8. Apache Storm is a distributed data processing engine designed for big data streaming processing and real-time analytics.

  9. Apache Spark Streaming
  10. Apache Spark Streaming is a real-time processing engine that enables high-throughput, fault-tolerant processing of streaming data from different sources.

  11. Apache HBase
  12. Apache HBase is a column-oriented NoSQL database designed to handle massive amounts of unstructured and semi-structured data.

  13. Apache Cassandra
  14. Apache Cassandra is another highly-scalable NoSQL database that is designed to handle massive amounts of read and write data operations with high availability across different data centers.

Big Data Architecture Diagram

The Big Data architecture diagram below shows an overview of the big data architecture layers, their respective components, and the flow of data processing:

Big Data Architecture Examples

The following are some examples of organizations that have successfully implemented Big Data architectures:


Netflix is a popular online streaming platform that uses big data analytics to provide personalized content and recommendations to its users. Netflix collects large amounts of data from its users, including their viewing history, ratings, and user profiles, to personalize the in-app experience for each user and help them discover new content more easily. Netflix's big data architecture utilizes an analytics platform that combines different tools, technologies, algorithms, and approaches to data processing. This technology includes the following:

  • Apaches Cassandra database
  • Elasticsearch for full-text search capabilities
  • Apache Kafka for real-time event processing
  • Apache Pig for ETL processing
  • Amazon EC2 and S3 for storage and computing resources


Walmart is a multinational retail corporation that uses big data analytics to gain valuable insights into its operations, products and customer behavior. Walmart collects and processes large amounts of data, including customer transactions, inventory levels, and supply-chain data. Walmart's big data architecture involves a distributed system that includes the following technology:

  • Apache Hadoop
  • IBM Netezza data warehousing appliance
  • PySpark for big data processing and analysis
  • Hive for data warehousing and analytics
  • Tableau for data visualization

Big Data Architecture Patterns PDF

Big Data Architecture Patterns refer to reusable designs that architects and developers can use to solve specific big data use cases and problems. The patterns provide a general solution for the same kind of problem appearing in different contexts. There are several resources available in the form of eBooks and PDFs, including the following:

  • Big Data Patterns and Use Cases - O'Reilly Media
  • The Big Data Architect's Handbook - Hadoop and Spark Best Practices
  • Big Data Analytics with R and Hadoop - Vignesh Prajapati
  • Big Data Black Book - Karthikeyan P
  • Big Data Architect's Guide to Apache Hadoop and Spark

Big Data Architecture Case Study

The following is a case study of how Starbucks implemented a big data architecture:


Starbucks is a popular coffee chain that uses big data and analytics to better understand its customer's behavior and preferences. Starbucks processes large amounts of customer data, including their purchases, usage, and feedback, to gain insights into the effectiveness of its marketing strategies and overall customer satisfaction. Starbucks big data architecture involves the following technology:

  • Apache Hadoop for storing and processing imported data
  • Teradata Aster Discovery Platform for data transformation and analysis
  • Tableau for data visualization
  • Apache Spark for processing and analysis of massive amounts of data

Starbucks' big data architecture allows it to gain actionable insights that enable them to improve their operations continually and provide a better customer experience.


Big Data architecture has proven to be an essential tool for modern organizations that require efficient processing, management, and analysis of massive data sets. The five identified layers of Big Data architecture are the foundation layer, ingestion layer, integration layer, analysis layer, and presentation layer. These layers form the basis for developing Big Data architecture, which involves using specialized tools and technology such as Hadoop, NoSQL databases, Apache Spark, and Apache Storm, among others. There are several resources available, including Big Data Patterns and Use Cases - O'Reilly Media and Big Data Analytics with R and Hadoop - Vignesh Prajapati, that showcase best practices and design patterns for developing big data architectures.

  • Share on Facebook
  • Share on Twitter
  • Share on LinkedIn
  • Share on WhatsApp

Learn More :

Top 10 Advantages of Big Data You Must Know - TechVidvan The Unparalleled Advantages of Big Data: Unlocking the Power of Data Analytics 30 May 2023 by Admin

Big data is a buzzword that refers to the vast and complex datasets that traditional data management tools are unable to handle. With the rise of digital technologies and the internet, data has become...

Upgrade your resume with the AWS Certified Big Data — Specialty ... AWS Big Data Certification: A Complete Guide to Everything You Need to Know 30 May 2023 by Admin


Big Data Applications - A manifestation of the hottest buzzword - DataFlair The Applications of Big Data: Theory and Practice 30 May 2023 by Admin

Big data has become one of the most talked-about technologies in recent years. The ability to process and analyze vast amounts of data has opened up a world of new possibilities and opportunities. Fro...

The Rise of the AI in Big Data Big Data and AI: A Transformational Shift in Various Fields 30 May 2023 by Admin


How to Be a Great Big Data Analyst - Revealed! - TechGenix The Role and Importance of Big Data Analysts in Today's Business World 30 May 2023 by Admin

With the ever-increasing amount of data generated by businesses and organizations, the role of big data analysts has become more critical than ever before. Big data analysts are the professionals in c...

The Buzz of Big Data - DZone Big Data Big Data Applications: Transforming Industries and Improving Lives 30 May 2023 by Admin

The amount of data being generated in the world today is growing at an unprecedented rate. From social media interactions to online purchases and electronic medical records, the variety, velocity, and...

Top 10 Big Data Tools for Analysis - TechVidvan The Comprehensive Guide to Big Data Analytics Tools 30 May 2023 by Admin

Every business generates a vast amount of data regularly. In recent years, the IT industry has seen a significant rise in the amount of data generation, and this data is growing at an unprecedented pa...

UC Berkeley Course Lectures: Analyzing Big Data With Twitter | Big data ... The Big Data Revolution at Berkeley 30 May 2023 by Admin


How to become a Big Data Analyst in 2023? | Intellipaat Blog Big Data Analyst Salary: Trends, Factors, and Comparison across Countries 30 May 2023 by Admin

The world has taken a huge turn towards the digital age, where data is considered the new oil. With the increasing usage and importance of data analytics and big data, the demand for big data analysts...

Big Data & Society | SAGE India The Era of Big Data and Society: Understanding its Impact on Our Lives 30 May 2023 by Admin

Big data has revolutionized the way we live our lives. From the way we shop to the way we communicate, big data has transformed the way we interact with the world around us. In the era of big data and...

Pragmatic Programming Techniques: BIG Data Analytics Pipeline The Power of Big Data Analysis and How It Empowers Businesses 30 May 2023 by Admin

In today's world, data is everything. Data has become a highly valuable asset for any organization that wants to succeed. How do organizations make sense of the enormous amount of data they generate o...

The What and Where of Big Data: A Data Definition Framework | 7wData Understanding Big Data Meaning: Analyzing the Phenomenon of Big Data 30 May 2023 by Admin

With the rapid advancements in technology, industries have been significantly transformed. One of the most impactful changes is the emergence of big data, which has revolutionized the way businesses o...

Big Data Overview - Types, Advantages, Characteristics Types of Big Data 30 May 2023 by Admin

With the growing influence of data in today’s world, it’s important to understand what types of big data exist. Big data is defined as an expansive collection of data that is too complex to be pro...

Big Data Engineer Salary Around the World - Developers, Designers ... The Rising Demand for Big Data Engineers in the Age of Information Overload 30 May 2023 by Admin

The following are some of the topics covered in a typical Big Data Engineering Syllabus:...

Big Data Hadoop Development Services | Hadoop Consulting and Solution Hadoop Big Data: Understanding the Basics 30 May 2023 by Admin

As technology keeps evolving, so does the amount of data generated on a daily basis. It's estimated that every single day, 2.5 quintillion bytes of data are created, and this number only keeps growin...

Big Data explicado a través de cinco sencillos gráficos Big Data Engineer Salary: What You Need to Know 30 May 2023 by Admin

The demand for big data engineers is on the rise as more and more companies recognize the importance of data-driven decision making. According to Glassdoor, big data engineers are among the top 15 hig...

Big Data technology infographic - Free PowerPoint Templates Characteristics of Big Data 30 May 2023 by Admin

Big data is a term that refers to large, complex, and unstructured data sets that are too difficult to process and analyze using traditional data processing tools and techniques. The characteristics o...

How Big Data Analytics Solving Product Promotion Issues Understanding Big Data Analytics: The Future of Data Analysis 30 May 2023 by Admin

The benefits of Big Data Analytics can be broken down into the following categories:...

Data visualization: definition, examples, tools, advice [guide 2021] What is an Example of Big Data? 30 May 2023 by Admin

Big data is a term used to describe the massive volume of structured and unstructured data that organizations generate on a daily basis. The sheer volume of data can be overwhelming and difficult to p...

Big Data Overview - Types, Advantages, Characteristics Big Data Definition: Understanding the Meaning, Benefits, and Challenges 30 May 2023 by Admin


Recent Post