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Xplenty VS Apache Airflow

Compare Xplenty VS Apache Airflow and see what are their differences

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Xplenty logo Xplenty

Xplenty is the #1 SecurETL - allowing you to build low-code data pipelines on the most secure and flexible data transformation platform. No longer worry about manual data transformations. Start your free 14-day trial now.

Apache Airflow logo Apache Airflow

Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
  • Xplenty Landing page
    Landing page //
    2023-09-18

Xplenty is a cloud-based ETL (extract, transform, load), ELT (extract, load, transform), and Reverse ETL data integration platform that easily unites multiple data sources. The Xplenty platform offers a simple, intuitive visual interface for building data pipelines between a large number of sources and destinations. Contact us for a free 14 day trial on the platform.

  • Apache Airflow Landing page
    Landing page //
    2023-06-17

Xplenty

Website
xplenty.com
$ Details
Free Trial
Platforms
Cloud Salesforce REST API
Release Date
2012 January
Startup details
Country
Israel
City
Tel Aviv
Employees
10 - 19
Edit details

Apache Airflow

Website
airflow.apache.org
$ Details
Platforms
-
Release Date
-
Edit details

Xplenty features and specs

  • Ease of Use
    Xplenty offers a user-friendly interface with a drag-and-drop feature that simplifies the process of data integration and transformation, making it accessible even for users with limited technical expertise.
  • Scalability
    Xplenty can handle large volumes of data and can scale according to your needs, ensuring performance remains consistent even as your data grows.
  • Integrations
    The platform supports a wide range of data sources and destinations, making it versatile for various data ecosystems. It seamlessly integrates with popular databases, cloud services, and data warehouses.
  • Support and Documentation
    Xplenty provides extensive documentation and customer support, including tutorials, webinars, and a responsive support team to assist you with any issues.
  • Customization
    Offers advanced features for custom transformations and workflows through scripting, allowing for greater flexibility in handling complex data integration tasks.

Possible disadvantages of Xplenty

  • Cost
    Xplenty can be expensive, particularly for small to mid-sized businesses. The pricing model is based on the number of connectors and data volume, which can add up quickly.
  • Learning Curve
    Although the interface is user-friendly, there may be a learning curve for new users to fully leverage the platform’s more advanced features and capabilities.
  • Performance
    Some users have reported performance issues, especially with large datasets, which can result in slower processing times compared to other ETL tools.
  • Limited Real-time Processing
    Xplenty is optimized for batch processing rather than real-time data integration, which may not be suitable for use cases requiring real-time data processing.
  • Dependence on Internet Connection
    As a cloud-based platform, Xplenty requires a stable internet connection. Any disruptions in connectivity can affect the ability to access and use the service.

Apache Airflow features and specs

  • Scalability
    Apache Airflow can scale horizontally, allowing it to handle large volumes of tasks and workflows by distributing the workload across multiple worker nodes.
  • Extensibility
    It supports custom plugins and operators, making it highly customizable to fit various use cases. Users can define their own tasks, sensors, and hooks.
  • Visualization
    Airflow provides an intuitive web interface for monitoring and managing workflows. The interface allows users to visualize DAGs, track task statuses, and debug failures.
  • Flexibility
    Workflows are defined using Python code, which offers a high degree of flexibility and programmatic control over the tasks and their dependencies.
  • Integrations
    Airflow has built-in integrations with a wide range of tools and services such as AWS, Google Cloud, and Apache Hadoop, making it easier to connect to external systems.

Possible disadvantages of Apache Airflow

  • Complexity
    Setting up and configuring Apache Airflow can be complex, particularly for new users. It requires careful management of infrastructure components like databases and web servers.
  • Resource Intensive
    Airflow can be resource-heavy in terms of both memory and CPU usage, especially when dealing with a large number of tasks and DAGs.
  • Learning Curve
    The learning curve can be steep for users who are not familiar with Python or the underlying concepts of workflow management.
  • Limited Real-Time Processing
    Airflow is better suited for batch processing and scheduled tasks rather than real-time event-based processing.
  • Dependency Management
    Managing task dependencies in complex DAGs can become cumbersome and may lead to configuration errors if not properly handled.

Analysis of Xplenty

Overall verdict

  • Xplenty is a good option for businesses looking for a reliable and user-friendly data integration platform, especially if they require extensive support for cloud-based data sources and flexibility in integration processes. However, as with any tool, the effectiveness of Xplenty depends on the specific needs and resources of the organization.

Why this product is good

  • Xplenty is a cloud-based data integration platform designed to simplify the complex processes of data preparation, transformation, and integration. It offers a user-friendly interface and a wide range of pre-built connectors, making it accessible for users without deep technical expertise. The platform supports ETL (Extract, Transform, Load) processes and can handle large volumes of data efficiently.

Recommended for

    Small to medium-sized businesses, teams without extensive technical expertise in data engineering, organizations needing to integrate data from multiple sources quickly, and those looking for a scalable cloud-based ETL solution.

Analysis of Apache Airflow

Overall verdict

  • Yes, Apache Airflow is a good choice for managing complex workflows and data pipelines, particularly for organizations that require a scalable and reliable orchestration tool.

Why this product is good

  • Apache Airflow is considered good because it provides a robust and flexible platform for authoring, scheduling, and monitoring workflows. It is open-source and has a large community that contributes to its continuous improvement. Airflow's modular architecture allows for easy integration with various data sources and destinations, and its UI is user-friendly, enabling effective pipeline visualization and management. Additionally, it offers extensibility through a wide array of plugins and customization options.

Recommended for

    Apache Airflow is recommended for data engineers, data scientists, and IT professionals who need to automate and manage workflows. It is particularly suited for organizations handling large-scale data processing tasks, requiring integration with various systems, and those looking to deploy machine learning pipelines or ETL processes.

Xplenty videos

+ Add

Xplenty - The Leading Data Integration Platform

More videos:

  • Demo - Create a Customer 360 View with Xplenty & Salesforce
  • Review - Xplenty Customer Story - CloudFactory

Apache Airflow videos

+ Add

Airflow Tutorial for Beginners - Full Course in 2 Hours 2022

Category Popularity

0-100% (relative to Xplenty and Apache Airflow)

Xplenty

Apache Airflow

Data Integration
100 100%
Data Integration
0% 0
Workflow Automation
0 0%
Workflow Automation
100% 100
ETL
100 100%
ETL
0% 0
Automation
0 0%
Automation
100% 100

User comments

Share your experience with using Xplenty and Apache Airflow. 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 Xplenty and Apache Airflow

Xplenty Reviews

Top 7 ETL Tools for 2021
Scalability, security, and excellent customer support are a few more advantages of Xplenty. For example, Xplenty has a new feature called Field Level Encryption, which allows users to encrypt and decrypt data fields using their own encryption key. Xplenty also makes sure to maintain regulatory compliance to laws like HIPPA, GDPR, and CCPA.
Source: www.xplenty.com
The 11 Best Low-Code Development Platforms
Xplenty is a low-code and no-code ETL (extract, transfer and load) data integration platform. It is made for both small, non-technical businesses and for deeply technical developers and engineers. It allows users to easily build data pipelines to and from over 100 data sources and destinations. Xplenty provides versatility, customization, and pre-built integrations to...
Source: www.xplenty.com
Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
Customer Story Keith connected multiple data sources with Amazon Redshift to transform, organize and analyze their customer data. Amazon Redshift Keith Slater Senior Developer at Creative Anvil Before we started with Xplenty, we were trying to move data from many different data sources into Redshift. Xplenty has helped us do that quickly and easily. The best feature of the...
Source: www.xplenty.com

Apache Airflow Reviews

5 Airflow Alternatives for Data Orchestration
While Apache Airflow continues to be a popular tool for data orchestration, the alternatives presented here offer a range of features and benefits that may better suit certain projects or team preferences. Whether you prioritize simplicity, code-centric design, or the integration of machine learning workflows, there is likely an alternative that meets your needs. By...
Source: www.kdnuggets.com
Top 8 Apache Airflow Alternatives in 2024
Apache Airflow is a workflow streamlining solution aiming at accelerating routine procedures. This article provides a detailed description of Apache Airflow as one of the most popular automation solutions. It also presents and compares alternatives to Airflow, their characteristic features, and recommended application areas. Based on that, each business could decide which...
Source: blog.skyvia.com
10 Best Airflow Alternatives for 2024
In a nutshell, you gained a basic understanding of Apache Airflow and its powerful features. On the other hand, you understood some of the limitations and disadvantages of Apache Airflow. Hence, this article helped you explore the best Apache Airflow Alternatives available in the market. So, you can try hands-on on these Airflow Alternatives and select the best according to...
Source: hevodata.com
A List of The 16 Best ETL Tools And Why To Choose Them
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows.
Source: www.datacamp.com
15 Best ETL Tools in 2022 (A Complete Updated List)
Apache Airflow programmatically creates, schedules and monitors workflows. It can also modify the scheduler to run the jobs as and when required.
Source: www.softwaretestinghelp.com

Social recommendations and mentions

Based on our record, Apache Airflow seems to be more popular. It has been mentiond 75 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.

Xplenty mentions (0)

We have not tracked any mentions of Xplenty yet. Tracking of Xplenty recommendations started around Mar 2021.

Apache Airflow mentions (75)

  • The DOJ Still Wants Google to Sell Off Chrome
    Is this really true? Something that can be supported by clear evidence? I’ve seen this trotted out many times, but it seems like there are interesting Apache projects: https://airflow.apache.org/ https://iceberg.apache.org/ https://kafka.apache.org/ https://superset.apache.org/. - Source: Hacker News / 3 months ago
  • 10 Must-Know Open Source Platform Engineering Tools for AI/ML Workflows
    Apache Airflow offers simplicity when it comes to scheduling, authoring, and monitoring ML workflows using Python. The tool's greatest advantage is its compatibility with any system or process you are running. This also eliminates manual intervention and increases team productivity, which aligns with the principles of Platform Engineering tools. - Source: dev.to / 4 months ago
  • Data Orchestration Tool Analysis: Airflow, Dagster, Flyte
    Data orchestration tools are key for managing data pipelines in modern workflows. When it comes to tools, Apache Airflow, Dagster, and Flyte are popular tools serving this need, but they serve different purposes and follow different philosophies. Choosing the right tool for your requirements is essential for scalability and efficiency. In this blog, I will compare Apache Airflow, Dagster, and Flyte, exploring... - Source: dev.to / 4 months ago
  • AIOps, DevOps, MLOps, LLMOps – What’s the Difference?
    Data pipelines: Apache Kafka and Airflow are often used for building data pipelines that can continuously feed data to models in production. - Source: dev.to / 5 months ago
  • Data Engineering with DLT and REST
    This article demonstrates how to work with near real-time and historical data using the dlt package. Whether you need to scale data access across the enterprise or provide historical data for post-event analysis, you can use the same framework to provide customer data. In a future article, I'll demonstrate how to use dlt with a workflow orchestrator such as Apache Airflow or Dagster.``. - Source: dev.to / 6 months ago
View more

What are some alternatives?

When comparing Xplenty and Apache Airflow, you can also consider the following products

Talend Data Integration - Talend offers open source middleware solutions that address big data integration, data management and application integration needs for businesses of all sizes.

Make.com - Tool for workflow automation (Former Integromat)

Matillion - Matillion is a cloud-based data integration software.

ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.

Talend Data Services Platform - Talend Data Services Platform is a single solution for data and application integration to deliver projects faster at a lower cost.

Microsoft Power Automate - Microsoft Power Automate is an automation platform that integrates DPA, RPA, and process mining. It lets you automate your organization at scale using low-code and AI.

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