Software Alternatives, Accelerators & Startups

Microsoft SQL Server VS Hadoop

Compare Microsoft SQL Server VS Hadoop and see what are their differences

Microsoft SQL Server logo Microsoft SQL Server

Microsoft Azure is an open, flexible, enterprise-grade cloud computing platform. Move faster, do more, and save money with IaaS + PaaS. Try for FREE.

Hadoop logo Hadoop

Open-source software for reliable, scalable, distributed computing
  • Microsoft SQL Server Landing page
    Landing page //
    2023-01-17
  • Hadoop Landing page
    Landing page //
    2021-09-17

Microsoft SQL Server features and specs

  • Performance
    Microsoft SQL Server offers high performance and efficient database management capabilities, optimized for both OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing).
  • Security Features
    SQL Server comes with advanced security features such as encryption, data masking, and advanced threat protection to ensure data integrity and privacy.
  • Scalability
    The server supports horizontal and vertical scaling to accommodate growing amounts of data and increasing number of users.
  • Integration with Microsoft Ecosystem
    Seamless integration with other Microsoft products such as Azure, Power BI, and Visual Studio, making it a versatile choice for businesses already using Microsoft services.
  • Ease of Use
    The server provides a user-friendly interface and helpful tools such as SQL Server Management Studio (SSMS) for database maintenance and management.
  • Comprehensive Support
    Microsoft offers extensive support and documentation, along with a strong community that provides additional resources and insights.

Possible disadvantages of Microsoft SQL Server

  • Cost
    Licensing and operational costs can be high, especially for larger enterprises, making it a significant investment.
  • Complexity
    Initial setup and configuration can be complex, often requiring expert knowledge to deploy and maintain effectively.
  • Resource Intensive
    The server can be resource-heavy, requiring significant hardware and computational resources to run efficiently, especially for larger databases.
  • Limited Cross-Platform Support
    Although improvements have been made, SQL Server is primarily optimized for Windows environments, which can limit its use in cross-platform scenarios.
  • Proprietary Software
    Being a proprietary software solution, it lacks the flexibility and cost benefits that come with open-source alternatives.
  • Updates and Patches
    Frequent updates and patches can sometimes disrupt service, requiring periodic maintenance that could result in downtime.

Hadoop features and specs

  • Scalability
    Hadoop can easily scale from a single server to thousands of machines, each offering local computation and storage.
  • Cost-Effective
    It utilizes a distributed infrastructure, allowing you to use low-cost commodity hardware to store and process large datasets.
  • Fault Tolerance
    Hadoop automatically maintains multiple copies of all data and can automatically recover data on failure of nodes, ensuring high availability.
  • Flexibility
    It can process a wide variety of structured and unstructured data, including logs, images, audio, video, and more.
  • Parallel Processing
    Hadoop's MapReduce framework enables the parallel processing of large datasets across a distributed cluster.
  • Community Support
    As an Apache project, Hadoop has robust community support and a vast ecosystem of related tools and extensions.

Possible disadvantages of Hadoop

  • Complexity
    Setting up, maintaining, and tuning a Hadoop cluster can be complex and often requires specialized knowledge.
  • Overhead
    The MapReduce model can introduce additional overhead, particularly for tasks that require low-latency processing.
  • Security
    While improvements have been made, Hadoop's security model is considered less mature compared to some other data processing systems.
  • Hardware Requirements
    Though it can run on commodity hardware, Hadoop can still require significant computational and storage resources for larger datasets.
  • Lack of Real-Time Processing
    Hadoop is mainly designed for batch processing and is not well-suited for real-time data analytics, which can be a limitation for certain applications.
  • Data Integrity
    Distributed systems face challenges in maintaining data integrity and consistency, and Hadoop is no exception.

Microsoft SQL Server videos

What is Microsoft SQL Server?

Hadoop videos

What is Big Data and Hadoop?

More videos:

  • Review - Product Ratings on Customer Reviews Using HADOOP.
  • Tutorial - Hadoop Tutorial For Beginners | Hadoop Ecosystem Explained in 20 min! - Frank Kane

Category Popularity

0-100% (relative to Microsoft SQL Server and Hadoop)
Databases
71 71%
29% 29
NoSQL Databases
88 88%
12% 12
Big Data
0 0%
100% 100
Relational Databases
81 81%
19% 19

User comments

Share your experience with using Microsoft SQL Server and Hadoop. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare Microsoft SQL Server and Hadoop

Microsoft SQL Server Reviews

20 Best SQL Management Tools in 2020
It is a SQL management tool for analysing the differences in Microsoft SQL Server database structures. It allows comparing database objects like tables, columns, indexes, foreign keys, schemas, etc.
Source: www.guru99.com

Hadoop Reviews

A List of The 16 Best ETL Tools And Why To Choose Them
Companies considering Hadoop should be aware of its costs. A significant portion of the cost of implementing Hadoop comes from the computing power required for processing and the expertise needed to maintain Hadoop ETL, rather than the tools or storage themselves.
16 Top Big Data Analytics Tools You Should Know About
Hadoop is an Apache open-source framework. Written in Java, Hadoop is an ecosystem of components that are primarily used to store, process, and analyze big data. The USP of Hadoop is it enables multiple types of analytic workloads to run on the same data, at the same time, and on a massive scale on industry-standard hardware.
5 Best-Performing Tools that Build Real-Time Data Pipeline
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than relying on hardware to deliver high-availability, the library itself is...

Social recommendations and mentions

Based on our record, Hadoop should be more popular than Microsoft SQL Server. It has been mentiond 23 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Microsoft SQL Server mentions (5)

  • Cloud provider comparison 2024: VM Performance / Price
    Azure is the #2 overall Cloud provider and, as expected, it's the best choice for most Microsoft/Windows-based solutions. That said, it does offer many types of Linux VMs, with quite similar abilities as AWS/GCP. - Source: dev.to / 9 months ago
  • Amdocs, NVIDIA and Microsoft Azure build custom LLMs for telcos
    Amdocs has partnered with NVIDIA and Microsoft Azure to build custom Large Language Models (LLMs) for the $1.7 trillion global telecoms industry. Source: over 1 year ago
  • Windows Azure: Microsoft's crown jewel
    You can utilise various tools on the platform to significantly improve your IT performance. Due to its flexibility, even official recommendations for Azure might need to be clarified and easier to comprehend. Simply put, Azure (formerly Windows Azure) is Microsoft's cloud computing operating system. Source: almost 2 years ago
  • From developer to (solutions) architect. A simple guide.
    This is not to say there aren't architects still working on premise in self managed environments, but if you're planning to join the forces, you probably want to have an idea of who are the 3 public cloud providers (AWS, Azure and GCP), and their offering and topology. - Source: dev.to / almost 4 years ago
  • Can You Learn AWS (And Get Certified) With No Experience? e.g. No IT background or degree
    Right now, AWS couldn’t be a better choice. AWS has been for many years—and continues to be—the market leader between all the cloud platforms. Whilst the competitors like GCP and Azure are catching up, they’ve still not toppled AWS which continues to be, by far, the biggest cloud provider. - Source: dev.to / about 4 years ago

Hadoop mentions (23)

  • India Open Source Development: Harnessing Collaborative Innovation for Global Impact
    Over the years, Indian developers have played increasingly vital roles in many international projects. From contributions to frameworks such as Kubernetes and Apache Hadoop to the emergence of homegrown platforms like OpenStack India, India has steadily carved out a global reputation as a powerhouse of open source talent. - Source: dev.to / 5 days ago
  • Unveiling the Apache License 2.0: A Deep Dive into Open Source Freedom
    One of the key attributes of Apache License 2.0 is its flexible nature. Permitting use in both proprietary and open source environments, it has become the go-to choice for innovative projects ranging from the Apache HTTP Server to large-scale initiatives like Apache Spark and Hadoop. This flexibility is not solely legal; it is also philosophical. The license is designed to encourage transparency and maintain a... - Source: dev.to / about 2 months ago
  • Apache Hadoop: Pioneering Open Source Innovation in Big Data
    Apache Hadoop is more than just software—it’s a full-fledged ecosystem built on the principles of open collaboration and decentralized governance. Born out of a need to process vast amounts of information efficiently, Hadoop uses a distributed file system and the MapReduce programming model to enable scalable, fault-tolerant computing. Central to its success is a diverse ecosystem that includes influential... - Source: dev.to / 2 months ago
  • Embracing the Future: India's Pioneering Journey in Open Source Development
    Navya: Designed to streamline administrative processes in educational institutions, Navya continues to demonstrate the power of open source in addressing local needs. Additionally, India’s vibrant tech communities are well represented on platforms like GitHub and SourceForge. These platforms host numerous Indian-led projects and serve as collaborative hubs for developers across diverse technology landscapes.... - Source: dev.to / 2 months ago
  • Where is Java Used in Industry?
    The rise of big data has seen Java arise as a crucial player in this domain. Tools like Hadoop and Apache Spark are built using Java, enabling businesses to process and analyze massive datasets efficiently. Java’s scalability and performance are critical for big data results that demand high trustability. - Source: dev.to / 5 months ago
View more

What are some alternatives?

When comparing Microsoft SQL Server and Hadoop, you can also consider the following products

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

Apache Storm - Apache Storm is a free and open source distributed realtime computation system.

MariaDB - An enhanced, drop-in replacement for MySQL