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Striim VS Apache Airflow

Compare Striim VS Apache Airflow and see what are their differences

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  3. » Reviews
  4. » Alternatives

Striim logo Striim

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

Apache Airflow logo Apache Airflow

Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
  • Striim Landing page
    Landing page //
    2023-10-20
  • Apache Airflow Landing page
    Landing page //
    2023-06-17

Striim features and specs

  • Real-time Data Integration
    Striim provides real-time data integration which allows users to ingest, process, and analyze data in real-time, offering timely insights for decision-making.
  • Wide Range of Connectors
    The platform supports a broad array of connectors for various data sources, including databases, cloud applications, and IoT devices, enabling seamless integration across different environments.
  • Scalability
    Striim’s architecture is designed to be highly scalable, allowing businesses to handle growing volumes of data without compromising on performance.
  • Low-latency Processing
    Striim enables low-latency data processing, ensuring that data is processed and available for analysis quickly, which is essential for time-sensitive applications.
  • User-friendly Interface
    The platform offers an intuitive, user-friendly interface that simplifies data flow creation and monitoring for users who may not have extensive technical expertise.

Possible disadvantages of Striim

  • Cost
    Striim could be expensive, especially for smaller organizations or startups with limited budgets, due to licensing and infrastructure costs.
  • Complexity
    The platform can be complex to set up and configure correctly, requiring technical expertise to fully leverage its capabilities.
  • Learning Curve
    New users might experience a steep learning curve due to the comprehensive feature set and sophisticated functionalities offered by Striim.
  • Dependence on Internet Connectivity
    While cloud-based, reliance on a stable internet connection can be a drawback for organizations with inconsistent network stability.

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 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.

Striim videos

+ Add

Striim On Premise to Azure Integration Step 1

More videos:

  • Review - Tech review: AwoX Striim LED Light Bulb
  • Review - Striim On Premise to Azure Integration Step 2

Apache Airflow videos

+ Add

Airflow Tutorial for Beginners - Full Course in 2 Hours 2022

Category Popularity

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

Striim

Apache Airflow

Development
100 100%
Development
0% 0
Workflow Automation
0 0%
Workflow Automation
100% 100
Backup & Sync
100 100%
Backup & Sync
0% 0
Automation
0 0%
Automation
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 Striim and Apache Airflow

Striim Reviews

Best ETL Tools: A Curated List
Striim is great for tasks that need complex stream processing and replication. It is well-known for its CDC features and strong support for Oracle databases. Striim competes with tools like Debezium and Estuary, especially in scalability. It is a top choice for environments that need both real-time and batch data processing.
Source: estuary.dev
Top 11 Fivetran Alternatives for 2024
Striim starts with Striim Developer, a free option of 10 million events per month with community support. Then it’s starting at $1,000 per month for deploying to BigQuery, Databricks, or Snowflake in real-time, or $2,000 per month for broader connector support. You also pay $0.75 (or $0.60) per virtual CPU-hour, and $10.10 per GB in or out. Mission Critical, which sounds...
Source: estuary.dev
Top 14 ETL Tools for 2023
Striim offers a real-time data integration platform for big data workloads. Users can integrate a wide variety of data sources and targets — including Oracle, SQL Server, MySQL, PostgreSQL, MongoDB, and Hadoop — in various file formats. Striim is compliant with data privacy regulations such as GDPR and HIPAA, and users can define pre-load transformations using SQL or Java.
Source: www.integrate.io
Top 7 ETL Tools for 2021
Striim offers a real-time data integration platform for big data workloads. Users can integrate a wide variety of data sources and targets in roughly 20 different file formats, including Oracle, SQL Server, MySQL, PostgreSQL, MongoDB, and Hadoop. Striim is compliant with data privacy regulations such as GDPR and HIPAA, and users can define pre-load transformations using SQL...
Source: www.xplenty.com
The 28 Best Data Integration Tools and Software for 2020
Description: Striim offers a real-time data integration solution that enables continuous query processing and streaming analytics. Striim integrates data from a wide variety of sources, including transaction/change data, events, log files, application and IoT sensor, and real-time correlation across multiple streams. The platform features pre-built data pipelines,...
Source: solutionsreview.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.

Striim mentions (0)

We have not tracked any mentions of Striim yet. Tracking of Striim 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
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What are some alternatives?

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

HVR - Your data. Where you need it. HVR is the leading independent real-time data replication solution that offers efficient data integration for cloud and more.

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

Bryteflow Data Replication and Integration - Bryteflow is a popular platform that offers many services, including data replication and integration.

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

alooma - alooma brings together a reliable data pipeline, an easy data transformation interface, and a powerful stream processor.

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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