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Apache NiFi VS Databricks

Compare Apache NiFi VS Databricks and see what are their differences

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Apache NiFi logo Apache NiFi

An easy to use, powerful, and reliable system to process and distribute data.

Databricks logo Databricks

Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?
  • Apache NiFi Landing page
    Landing page //
    2019-01-17
  • Databricks Landing page
    Landing page //
    2023-09-14

Apache NiFi features and specs

  • User-Friendly Interface
    Apache NiFi offers a drag-and-drop interface for designing data flows, making it easy to use even for those without extensive coding experience.
  • Extensive Connector Support
    NiFi comes with a wide range of pre-built connectors for various data sources and destinations, simplifying integration tasks.
  • Real-time Data Processing
    NiFi supports real-time data ingestion and processing, enabling timely data flow management.
  • Scalability
    Designed to be highly scalable, NiFi can handle both small and large data volumes, adjusting to organizational needs as they grow.
  • Flexible Data Routing
    NiFi allows dynamic routing of data based on content, making it versatile for various data transformation and routing needs.
  • Visual Data Monitoring
    It offers real-time monitoring of data flows with visual representations, aiding in quick issue identification and resolution.

Possible disadvantages of Apache NiFi

  • Resource Intensive
    Running NiFi can be resource-intensive, requiring substantial CPU and memory, especially for large-scale operations.
  • Complexity for Advanced Operations
    While straightforward for basic tasks, more complex workflows can become challenging and may require deeper technical expertise.
  • Security Management
    Although NiFi includes security features, configuring and maintaining a secure environment can be complex and time-consuming.
  • Limited Community Support
    As a specialized tool, the user community and available online resources are smaller compared to more widespread software solutions.
  • Learning Curve
    New users may face a steep learning curve, particularly when dealing with advanced features and custom processor development.
  • Licensing Costs for Enterprise Features
    Additional enterprise features and support offered by commercial versions may incur extra costs, potentially increasing the total cost of ownership.

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.

Analysis of Apache NiFi

Overall verdict

  • Overall, Apache NiFi is considered a robust and flexible tool for managing data flows efficiently. It offers a comprehensive set of features for developers and data engineers looking to simplify and automate their data processing tasks. However, it may not be the best fit for every use case, particularly for those with simpler requirements or who prefer a lightweight tool.

Why this product is good

  • Apache NiFi is an open-source software project designed to automate the flow of data between systems. It is known for its user-friendly interface, powerful data routing and transformation capabilities, and strong support for data provenance. Its ability to handle real-time data streams makes it suitable for complex data workflows, including those requiring data ingestion, distribution, and transformation.

Recommended for

  • Organizations with complex data integration and processing needs
  • Data engineers seeking automation of data flows
  • Developers who need a scalable and reliable data flow management tool
  • Teams requiring real-time data processing and powerful data provenance capabilities
  • Businesses looking for an open-source solution to manage data pipelines

Apache NiFi videos

+ Add

Forget Duplicating Local Changes: Apache NiFi and the Flow Development Lifecycle (FDLC)

Databricks videos

+ Add

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 Apache NiFi and Databricks)

Apache NiFi

Databricks

Analytics
100 100%
Analytics
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Data Integration
100 100%
Data Integration
0% 0
Big Data Analytics
0 0%
Big Data Analytics
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 Apache NiFi and Databricks

Apache NiFi Reviews

Top 8 Apache Airflow Alternatives in 2024
Another product by Apache is called NiFi – even though it’s also dedicated to data workflow management, it differs from Apache Airflow in many aspects. First of all, Apache NiFi is a completely web-based tool with a drag&drop interface and no coding. It’s easy to add and configure processors as graph nodes of data workflow, set up routing directions as graph edges, and...
Source: blog.skyvia.com
11 Best FREE Open-Source ETL Tools in 2024
Apache NiFi allows you to automate and manage the flow of information systems. It also enables NiFi to be an effective platform for building scalable and powerful dataflows. NiFi follows the fundamental concept of Flow-Based Programming. It has a highly configurable web-based UI, and houses features such as Data Provenance, Extensibility, and Security features.
Source: hevodata.com
10 Best Airflow Alternatives for 2024
Apache NiFi is a free and open-source application that automates data transfer across systems. The application comes with a web-based user interface to manage scalable directed graphs of data routing, transformation, and system mediation logic. It is a sophisticated and reliable data processing and distribution system. To edit data at runtime, it provides a highly flexible...
Source: hevodata.com
15 Best ETL Tools in 2022 (A Complete Updated List)
Apache Nifi simplifies the data flow between various systems using automation. The data flows consist of processors and a user can create their own processors. These flows can be saved as templates and later can be integrated with more complex flows. These complex flows can then be deployed to multiple servers with minimal efforts.
Source: www.softwaretestinghelp.com
Top 10 Popular Open-Source ETL Tools for 2021
Apache NiFi allows you to automate and manage the flow of information systems. It also enables NiFi to be an effective platform for building scalable and powerful dataflows. NiFi follows the fundamental concept of Flow-Based Programming. It has a highly configurable web-based UI, and houses features such as Data Provenance, Extensibility, and Security features.
Source: hevodata.com

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

Databricks might be a bit more popular than Apache NiFi. We know about 18 links to it since March 2021 and only 18 links to Apache NiFi. 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.

Apache NiFi mentions (18)

  • NSA Ghidra open-source reverse engineering framework
    They also contributed Apache NiFi but that was much earlier: https://nifi.apache.org/. - Source: Hacker News / 12 months ago
  • Workbench for Apache NiFi data flows
    This article presents the concept and implementation of a universal workbench for Apache NiFi data flows. - Source: dev.to / about 1 year ago
  • Ask HN: What low code platforms are worth using?
    Apache NIFI (https://nifi.apache.org/). It uses the concept of Flow-based programming. Also its so underacknolged but this tool is very flexible. I have used as an Event Bus all the 3rd-Party Integrations. - Source: Hacker News / over 1 year ago
  • Help with choosing techstack for a new DE team
    Presently setting up Apache Nifi + Apache MiNiFi for the ETL portion of my work. NiFi was easy enough to figure out; but the docs for MiNiFi have been a pain due to differences between the Java and C++ versions. I then entirely configured it with the Java version so that it was easier to search for answers for the MiNiFi yaml syntax. Source: almost 2 years ago
  • Json splitting and Rerouting (new to nifi)
    NIFI, like most Apache projects does most of its discussion on its mailing lists, but also has a slack. Source: about 2 years ago
View more

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 / 8 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 / almost 3 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 Apache NiFi and Databricks, you can also consider the following products

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

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

Histats - Start tracking your visitors in 1 minute!

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.

AFSAnalytics - AFSAnalytics.

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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