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SAP Data Management VS Databricks

Compare SAP Data Management VS Databricks and see what are their differences

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SAP Data Management logo SAP Data Management

Sap Data Management is a flagship enterprise information management solution that facilities the organizations to manage data quality, migration of data, text analytics, and interconnectivity with both SAP and non-SAP system.

Databricks logo Databricks

Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?
  • SAP Data Management Landing page
    Landing page //
    2023-08-22
  • Databricks Landing page
    Landing page //
    2023-09-14

SAP Data Management features and specs

  • Scalability
    SAP Data Management solutions are designed to scale with your business. They can handle vast amounts of data and are suitable for large enterprises as well as growing companies.
  • Integration
    SAP's Data Management tools offer seamless integration with other SAP applications and third-party systems, ensuring a unified data environment.
  • Real-time Data Processing
    One of the key features is real-time data processing, which enhances decision-making and enables businesses to react quickly to changing conditions.
  • Comprehensive Analytics
    The robust analytics tools within the SAP suite provide deep insights into your data, helping businesses to identify trends, make predictions, and optimize operations.
  • Data Security
    SAP places a strong emphasis on data security, with built-in features to ensure data integrity, confidentiality, and compliance with regulatory requirements.
  • Support and Community
    SAP provides extensive support and has a large user community, which can be very beneficial for troubleshooting and optimizing the use of their data management tools.

Possible disadvantages of SAP Data Management

  • Cost
    SAP solutions can be expensive to implement and maintain, making them less accessible for small businesses or startups with limited budgets.
  • Complexity
    The extensive feature set and capabilities can make SAP Data Management tools complex to configure and use, often requiring specialized knowledge and training.
  • Implementation Time
    Deploying SAP Data Management solutions can be time-consuming, often requiring months of planning, customization, and integration.
  • Resource Intensive
    Running SAP Data Management tools effectively can require significant IT resources, including powerful hardware and skilled personnel.
  • Customization Challenges
    While highly customizable, SAP’s systems can be difficult to tailor exactly to a company’s specific needs without extensive development work.

Databricks features and specs

  • Unified Data Analytics Platform
    Databricks integrates various data processing and analytics tools, offering a unified environment for data engineering, machine learning, and business analytics. This integration can streamline workflows and reduce the complexity of data management.
  • Scalability
    Databricks leverages Apache Spark and other scalable technologies to handle large datasets and high computational workloads efficiently. This makes it suitable for enterprises with significant data processing needs.
  • Collaborative Environment
    The platform offers collaborative notebooks that allow data scientists, engineers, and analysts to work together in real-time. This enhances productivity and fosters better communication within teams.
  • Performance Optimization
    Databricks includes various performance optimization features such as caching, indexing, and query optimization, which can significantly speed up data processing tasks.
  • Support for Various Data Formats
    The platform supports a wide range of data formats and sources, including structured, semi-structured, and unstructured data, making it versatile and adaptable to different use cases.
  • Integration with Cloud Providers
    Databricks is designed to work seamlessly with major cloud providers like AWS, Azure, and Google Cloud, allowing users to easily integrate it into their existing cloud infrastructure.

Possible disadvantages of Databricks

  • Cost
    Databricks can be expensive, especially for large-scale deployments or high-frequency usage. It may not be the most cost-effective solution for smaller organizations or projects with limited budgets.
  • Complexity
    While powerful, Databricks can be complex to set up and manage, requiring specialized knowledge in Apache Spark and cloud infrastructure. This might lead to a steeper learning curve for new users.
  • Dependency on Cloud Providers
    Being heavily integrated with cloud providers, Databricks might face issues like vendor lock-in, where switching providers becomes difficult or costly.
  • Limited Offline Capabilities
    Databricks is primarily designed for cloud environments, which means offline or on-premise capabilities are limited, posing challenges for organizations with strict data governance policies.
  • Resource Management
    Efficiently managing and allocating resources can be challenging in Databricks, especially in large multi-user environments. Mismanagement of resources could lead to increased costs and reduced performance.

SAP Data Management videos

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Databricks videos

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Introduction to Databricks

More videos:

  • Tutorial - Azure Databricks Tutorial | Data transformations at scale
  • Review - Databricks - Data Movement and Query

Category Popularity

0-100% (relative to SAP Data Management and Databricks)

SAP Data Management

Databricks

OS & Utilities
100 100%
OS & Utilities
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Data Integration
100 100%
Data Integration
0% 0
Database Tools
0 0%
Database Tools
100% 100

User comments

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Reviews

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

SAP Data Management Reviews

We have no reviews of SAP Data Management yet.
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Databricks Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Databricks notebooks are a popular tool for developing code and presenting findings in data science and machine learning. Databricks Notebooks support real-time multilingual coauthoring, automatic versioning, and built-in data visualizations.
Source: lakefs.io
7 best Colab alternatives in 2023
Databricks is a platform built around Apache Spark, an open-source, distributed computing system. The Databricks Community Edition offers a collaborative workspace where users can create Jupyter notebooks. Although it doesn't offer free GPU resources, it's an excellent tool for distributed data processing and big data analytics.
Source: deepnote.com
Top 5 Cloud Data Warehouses in 2023
Jan 11, 2023 The 5 best cloud data warehouse solutions in 2023Google BigQuerySource: https://cloud.google.com/bigqueryBest for:Top features:Pros:Cons:Pricing:SnowflakeBest for:Top features:Pros:Cons:Pricing:Amazon RedshiftSource: https://aws.amazon.com/redshift/Best for:Top features:Pros:Cons:Pricing:FireboltSource: https://www.firebolt.io/Best for:Top...
Source: www.shipyardapp.com
Top 10 AWS ETL Tools and How to Choose the Best One | Visual Flow
Databricks is a simple, fast, and collaborative analytics platform based on Apache Spark with ETL capabilities. It accelerates innovation by bringing together data science and data science businesses. It is a fully managed open-source version of Apache Spark analytics with optimized connectors to storage platforms for the fastest data access.
Source: visual-flow.com
Top Big Data Tools For 2021
Now Azure Databricks achieves 50 times better performance thanks to a highly optimized version of Spark. Databricks also enables real-time co-authoring and automates versioning. Besides, it features runtimes optimized for machine learning that include many popular libraries, such as PyTorch, TensorFlow, Keras, etc.
Source: blog.bismart.com

Social recommendations and mentions

Based on our record, Databricks seems to be more popular. It has been mentiond 18 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 Management mentions (0)

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

Databricks mentions (18)

  • Platform Engineering Abstraction: How to Scale IaC for Enterprise
    Vendors like Confluent, Snowflake, Databricks, and dbt are improving the developer experience with more automation and integrations, but they often operate independently. This fragmentation makes standardizing multi-directional integrations across identity and access management, data governance, security, and cost control even more challenging. Developing a standardized, secure, and scalable solution for... - Source: dev.to / 7 months ago
  • dolly-v2-12b
    Dolly-v2-12bis a 12 billion parameter causal language model created by Databricks that is derived from EleutherAI’s Pythia-12b and fine-tuned on a ~15K record instruction corpus generated by Databricks employees and released under a permissive license (CC-BY-SA). Source: about 2 years ago
  • Clickstream data analysis with Databricks and Redpanda
    Global organizations need a way to process the massive amounts of data they produce for real-time decision making. They often utilize event-streaming tools like Redpanda with stream-processing tools like Databricks for this purpose. - Source: dev.to / over 2 years ago
  • DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
    Databricks, a data lakehouse company founded by the creators of Apache Spark, published a blog post claiming that it set a new data warehousing performance record in 100 TB TPC-DS benchmark. It was also mentioned that Databricks was 2.7x faster and 12x better in terms of price performance compared to Snowflake. - Source: dev.to / almost 3 years ago
  • A Quick Start to Databricks on AWS
    Go to Databricks and click the Try Databricks button. Fill in the form and Select AWS as your desired platform afterward. - Source: dev.to / about 3 years ago
View more

What are some alternatives?

When comparing SAP Data Management and Databricks, you can also consider the following products

Ataccama - We deliver Self-Driving Data Management & Governance with Ataccama ONE. It’s a fully integrated yet modular platform for any data, user, domain, or deployment.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Dell EMC DataIQ - Dell EMC DataIQ is one of the unique storage monitoring and dataset management software for unstructured data that allows a unified file system of PowerScale, ECS, and delivers unique insights into data usage and storage system health.

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

1010Data - 1010data provides cloud-based big data analytics for retail, manufacturing, telecom and financial services enterprises.

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

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