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SAP Data Services VS Hadoop

Compare SAP Data Services VS Hadoop and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

SAP Data Services logo SAP Data Services

SAP Data Services provides functionality for data integration, quality, cleansing, and more.

Hadoop logo Hadoop

Open-source software for reliable, scalable, distributed computing
  • SAP Data Services Landing page
    Landing page //
    2023-10-21
  • Hadoop Landing page
    Landing page //
    2021-09-17

SAP Data Services features and specs

  • Robust Data Integration
    SAP Data Services provides powerful data integration capabilities that allow organizations to access, transform, and integrate data from a variety of sources. This enables seamless data flow and supports comprehensive data-driven decision making.
  • Data Quality Management
    The platform includes advanced data quality features, enabling users to cleanse and enrich data, ensuring accuracy and consistency across business processes. This helps enhance trust in the data used for critical business operations.
  • Scalability
    SAP Data Services is designed to handle large volumes of data, making it suitable for organizations of all sizes. It supports complex data environments and can scale to meet growing business requirements.
  • Integration with SAP Ecosystem
    The tool seamlessly integrates with other SAP products and solutions, enabling businesses to leverage their existing SAP investments for improved performance and business insight.
  • Comprehensive Transformation Features
    SAP Data Services offers an array of data transformation functionalities that allow for complex data processing and manipulation, supporting diverse business needs and scenarios.

Possible disadvantages of SAP Data Services

  • Complexity
    The robust feature set of SAP Data Services can also lead to increased complexity in setup and operation. Users might require extensive training and expertise to utilize the full capabilities of the software.
  • Cost
    For some businesses, particularly smaller ones, the cost associated with deploying and maintaining SAP Data Services can be substantial. This can be a barrier to entry for some organizations.
  • Resource Intensive
    Running SAP Data Services can be resource-intensive, requiring substantial hardware and IT resources, which can impact overall IT infrastructure and budgeting.
  • Steep Learning Curve
    Users may encounter a steep learning curve, given the complex and extensive functionalities of SAP Data Services. This can delay implementation and require ongoing support and training.
  • Integration Complexity with Non-SAP Systems
    While it integrates well within the SAP ecosystem, integrating SAP Data Services with non-SAP systems can be challenging and may require additional custom development or third-party tools.

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.

Analysis of Hadoop

Overall verdict

  • Hadoop is a robust and powerful data processing platform that is well-suited for organizations that need to manage and analyze large-scale data. Its resilience, scalability, and open-source nature make it a popular choice for big data solutions. However, it may not be the best fit for all use cases, especially those requiring real-time processing or where ease of use is a priority.

Why this product is good

  • Hadoop is renowned for its ability to store and process large datasets using a distributed computing model. It is scalable, cost-effective, and efficient in handling massive volumes of data across clusters of computers. Its ecosystem includes a wide range of tools and technologies like HDFS, MapReduce, YARN, and Hive that enhance data processing and analysis capabilities.

Recommended for

  • Organizations dealing with vast amounts of data needing efficient batch processing.
  • Businesses that require scalable storage solutions to manage their data growth.
  • Companies interested in leveraging a diverse ecosystem of data processing tools and technologies.
  • Technical teams that have the expertise to manage and optimize complex distributed systems.

SAP Data Services videos

+ Add

SAP Data Services Overview (Introduction)

Hadoop videos

+ Add

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 SAP Data Services and Hadoop)

SAP Data Services

Hadoop

Backup & Sync
100 100%
Backup & Sync
0% 0
Databases
0 0%
Databases
100% 100
Business & Commerce
100 100%
Business & Commerce
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using SAP Data Services and Hadoop. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare SAP Data Services and Hadoop

SAP Data Services Reviews

Best ETL Tools: A Curated List
SAP acquired Business Objects in 2007, and it became SAP Data Services. It is designed to manage complex data environments, including SAP systems, but it also supports non-SAP systems, cloud services, and extensive data processing platforms. With its focus on data quality, advanced transformations, and scalability, SAP Data Services is an enterprise-ready solution for...
Source: estuary.dev
A List of The 16 Best ETL Tools And Why To Choose Them
In conclusion, there are many different ETL and data integration tools available, each with its own unique features and capabilities. Some popular options include SSIS, Talend Open Studio, Pentaho Data Integration, Hadoop, Airflow, AWS Data Pipeline, Google Dataflow, SAP BusinessObjects Data Services, and Hevo. Companies considering these tools should carefully evaluate...
Source: www.datacamp.com
15 Best ETL Tools in 2022 (A Complete Updated List)
Using SAP BusinessObjects Data Integrator, data can be extracted from any source and loaded into any data warehouse.
Source: www.softwaretestinghelp.com
The 28 Best Data Integration Tools and Software for 2020
Description: SAP provides on-prem and cloud integration functionality through two main channels. Traditional capabilities are offered through SAP Data Services, a data management platform that provides capabilities for data integration, quality, and cleansing. Integration Platform as a Service features are available through the SAP Cloud Platform. SAP’s Cloud Platform...
Source: solutionsreview.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.
Source: www.datacamp.com
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.
Source: www.analytixlabs.co.in
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...
Source: www.analyticsinsight.net

Social recommendations and mentions

Based on our record, Hadoop seems to be more popular. It has been mentiond 26 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.

SAP Data Services mentions (0)

We have not tracked any mentions of SAP Data Services yet. Tracking of SAP Data Services recommendations started around Mar 2021.

Hadoop mentions (26)

  • JuiceFS 1.3 Beta 2 Integrates Apache Ranger for Fine-Grained Access Control
    To simplify ​​fine-grained permission management​​ and enable centralized ​​web-based administration​​, JuiceFS now supports ​​Apache Ranger​​, a widely adopted security framework in the Hadoop ecosystem. - Source: dev.to / 4 months ago
  • Apache Hadoop: Open Source Business Model, Funding, and Community
    This post provides an in‐depth look at Apache Hadoop, a transformative distributed computing framework built on an open source business model. We explore its history, innovative open funding strategies, the influence of the Apache License 2.0, and the vibrant community that drives its continuous evolution. Additionally, we examine practical use cases, upcoming challenges in scaling big data processing, and future... - Source: dev.to / 5 months ago
  • What is Apache Kafka? The Open Source Business Model, Funding, and Community
    Modular Integration: Thanks to its modular approach, Kafka integrates seamlessly with other systems including container orchestration platforms like Kubernetes and third-party tools such as Apache Hadoop. - Source: dev.to / 5 months ago
  • 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 months 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 / 7 months ago
View more

What are some alternatives?

When comparing SAP Data Services and Hadoop, you can also consider the following products

Striim - Striim provides an end-to-end, real-time data integration and streaming analytics platform.

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

Oracle Data Integrator - Oracle Data Integrator is a data integration platform that covers batch loads, to trickle-feed integration processes.

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

SQL Server Integration Services - Learn about SQL Server Integration Services, Microsoft's platform for building enterprise-level data integration and data transformations solutions

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

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