Software Alternatives, Accelerators & Startups

Metabase VS Google Cloud Dataflow

Compare Metabase VS Google Cloud Dataflow and see what are their differences

Metabase logo Metabase

Metabase is the easy, open source way for everyone in your company to ask questions and learn from...

Google Cloud Dataflow logo Google Cloud Dataflow

Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
  • Metabase Landing page
    Landing page //
    2024-10-22
  • Google Cloud Dataflow Landing page
    Landing page //
    2023-10-03

Metabase features and specs

  • Ease of Use
    Metabase offers an intuitive and user-friendly interface, which makes it easy for non-technical users to generate and analyze reports without requiring SQL knowledge.
  • Open Source
    Being open-source, Metabase allows organizations to customize and extend the tool according to their needs, and it can be self-hosted to retain full control over data.
  • Quick Setup
    Deploying Metabase is straightforward and can be accomplished quickly, enabling teams to start analyzing data almost immediately.
  • Integrations
    Metabase integrates with a wide array of databases and data sources, making it versatile for organizations with diverse data environments.
  • Visualization Options
    It provides a variety of visualization options, from simple charts to complex dashboards, to help users better understand their data.
  • Community Support
    As an open-source project, Metabase has a strong community that contributes to its development and offers support through forums and documentation.
  • Embedded Analytics
    Metabase offers an embedded analytics feature which allows organizations to integrate dashboards and reports into their own applications.

Possible disadvantages of Metabase

  • Limited Advanced Analytics
    While great for basic reporting, Metabase lacks some of the advanced analytics capabilities offered by more specialized BI tools.
  • Scaling Issues
    Metabase might face performance issues as data volume and user base grow, making it less suitable for very large-scale deployments without significant optimization.
  • Customization Limitations
    Even though Metabase is open-source, some users find its customization options limited compared to other BI tools, especially regarding dashboard design.
  • Security Features
    The platform's security features are not as robust as those of some enterprise-level BI tools, potentially requiring additional measures for highly sensitive data.
  • Dependency on Third-Party Services
    For certain features, Metabase may rely on third-party services, which could introduce additional points of failure and dependency.
  • Limited Collaboration Tools
    Collaboration features are somewhat basic compared to those offered by more comprehensive BI platforms, possibly making teamwork less efficient.
  • No Mobile App
    Metabase does not offer a dedicated mobile app, which could be a limitation for users who need to access dashboards and reports on the go.

Google Cloud Dataflow features and specs

  • Scalability
    Google Cloud Dataflow can automatically scale up or down depending on your data processing needs, handling massive datasets with ease.
  • Fully Managed
    Dataflow is a fully managed service, which means you don't have to worry about managing the underlying infrastructure.
  • Unified Programming Model
    It provides a single programming model for both batch and streaming data processing using Apache Beam, simplifying the development process.
  • Integration
    Seamlessly integrates with other Google Cloud services like BigQuery, Cloud Storage, and Bigtable.
  • Real-time Analytics
    Supports real-time data processing, enabling quicker insights and facilitating faster decision-making.
  • Cost Efficiency
    Pay-as-you-go pricing model ensures you only pay for resources you actually use, which can be cost-effective.
  • Global Availability
    Cloud Dataflow is available globally, which allows for regionalized data processing.
  • Fault Tolerance
    Built-in fault tolerance mechanisms help ensure uninterrupted data processing.

Possible disadvantages of Google Cloud Dataflow

  • Steep Learning Curve
    The complexity of using Apache Beam and understanding its model can be challenging for beginners.
  • Debugging Difficulties
    Debugging data processing pipelines can be complex and time-consuming, especially for large-scale data flows.
  • Cost Management
    While it can be cost-efficient, the costs can rise quickly if not monitored properly, particularly with real-time data processing.
  • Vendor Lock-in
    Using Google Cloud Dataflow can lead to vendor lock-in, making it challenging to migrate to another cloud provider.
  • Limited Support for Non-Google Services
    While it integrates well within Google Cloud, support for non-Google services may not be as robust.
  • Latency
    There can be some latency in data processing, especially when dealing with high volumes of data.
  • Complexity in Pipeline Design
    Designing pipelines to be efficient and cost-effective can be complex, requiring significant expertise.

Metabase videos

What is Metabase?

More videos:

  • Demo - See Metabase in action in 5 mins
  • Review - Metabase vs Apache Superset: Which is best for your team?
  • Review - Metabase vs Tableau: Which is better for your team
  • Review - Metabase vs. Looker: Which is best for your team?

Google Cloud Dataflow videos

Introduction to Google Cloud Dataflow - Course Introduction

More videos:

  • Review - Serverless data processing with Google Cloud Dataflow (Google Cloud Next '17)
  • Review - Apache Beam and Google Cloud Dataflow

Category Popularity

0-100% (relative to Metabase and Google Cloud Dataflow)
Data Dashboard
66 66%
34% 34
Big Data
0 0%
100% 100
Business Intelligence
100 100%
0% 0
Data Visualization
100 100%
0% 0

User comments

Share your experience with using Metabase and Google Cloud Dataflow. 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 Metabase and Google Cloud Dataflow

Metabase Reviews

Explore 6 Metabase Alternatives for Data Visualization and Analysis
Draxlr is an intuitive Metabase alternative, blending a robust no-code query builder with AI-powered SQL generation for both non-technical and advanced users. It seamlessly integrates with various databases and provides real-time alerts through Slack, email, and more. With features like embeddable dashboards, granular team access, customizable visualizations, and live data...
Source: www.draxlr.com
5 best Looker alternatives
Metabase: Metabase is an open-source BI tool that offers a free self-hosted plan, but this can be challenging for non-technical users who may struggle with setup and maintenance. While the cloud-hosted option simplifies that, it comes at a higher cost, which might not be ideal for smaller teams or businesses.
Source: www.draxlr.com
10 Best Alternatives to Looker in 2024
Metabase: Metabase is a popular open-source alternative known for its cost-effectiveness and ease of setup. Its simplicity and straightforward deployment make it particularly appealing to smaller businesses and startups.
6 Best Looker alternatives
If you’re considering Metabase, take a look at our deepdive into Looker vs Metabase, as well as a breakdown of top Metabase alternatives.
Source: trevor.io
10 Best Looker Alternatives in 2024 | A Practitioner Review
While Metabase may not offer the same depth in modeling features or the proprietary semantic layer (LookML) that Looker does, it can integrate with Cube.dev to provide a viable, modern, open-source alternative. Additionally, Metabase's alert feature and its general adequacy for IT-related reporting present a valuable, lightweight solution for teams not requiring the full...

Google Cloud Dataflow Reviews

Top 8 Apache Airflow Alternatives in 2024
Google Cloud Dataflow is highly focused on real-time streaming data and batch data processing from web resources, IoT devices, etc. Data gets cleansed and filtered as Dataflow implements Apache Beam to simplify large-scale data processing. Such prepared data is ready for analysis for Google BigQuery or other analytics tools for prediction, personalization, and other purposes.
Source: blog.skyvia.com

Social recommendations and mentions

Metabase might be a bit more popular than Google Cloud Dataflow. We know about 17 links to it since March 2021 and only 14 links to Google Cloud Dataflow. 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.

Metabase mentions (17)

  • Ask HN: Who is hiring? (April 2025)
    Metabase | https://metabase.com/ | Remote (Global) | Full-time | Applied AI Engineers, Engineering Managers, Frontend and Backend Engineers Metabase is an open source (https://github.com/metabase/metabase) business intelligence software that lets anyone in your company rummage around in the databases you have. It connects to a number of databases / data warehouses (BigQuery, Redshift, Snowflake, Postgres, MySQL,... - Source: Hacker News / about 1 month ago
  • Ask HN: Who is hiring? (September 2024)
    Metabase | https://metabase.com | REMOTE | Full-time | Backend Engineers, Frontend Engineers, and Engineering Managers Metabase is open source analytics software that lets anyone in your company rummage around in the databases you have. It connects to a number of databases / data warehouses (BigQuery, Redshift, Snowflake, Postgres, MySQL, etc). People rather like the product (https://metabase.com/love). We're a... - Source: Hacker News / 8 months ago
  • Tools for Starting a Business or Testing an Idea: A Beginner's Guide
    Reporting - Metabase A free, open-source business intelligence tool that helps you create custom reports and dashboards to track your business metrics and make data-driven decisions. - Source: dev.to / 9 months ago
  • Is Tableau Dead?
    I've never used Tableau, but heard a lot of hate about it. However, in my previous role, we were big fans of Metabase (https://metabase.com). You can also self-host it, which was a huge win for us. - Source: Hacker News / about 1 year ago
  • Ask HN: Open-Source Self-Hosted No-Code Platforms?
    The solution really depends on what sort of problems you are trying to solve and who your customers are. There are a fair few low-code solutions out there for reporting and data visualisation that are great for finance and marketing teams for example. e.g. https://metabase.com/ , https://evidence.dev/ For enterprise processes I'd go with Camunda (solely based on recommendations and not first hand experience).... - Source: Hacker News / about 2 years ago
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Google Cloud Dataflow mentions (14)

  • How do you implement CDC in your organization
    Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: over 2 years ago
  • Here’s a playlist of 7 hours of music I use to focus when I’m coding/developing. Post yours as well if you also have one!
    This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: over 2 years ago
  • How are view/listen counts rolled up on something like Spotify/YouTube?
    I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: over 2 years ago
  • Best way to export several GCP datasets to AWS?
    You can run a Dataflow job that copies the data directly from BQ into S3, though you'll have to run a job per table. This can be somewhat expensive to do. Source: over 2 years ago
  • Why we don’t use Spark
    It was clear we needed something that was built specifically for our big-data SaaS requirements. Dataflow was our first idea, as the service is fully managed, highly scalable, fairly reliable and has a unified model for streaming & batch workloads. Sadly, the cost of this service was quite large. Secondly, at that moment in time, the service only accepted Java implementations, of which we had little knowledge... - Source: dev.to / about 3 years ago
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What are some alternatives?

When comparing Metabase and Google Cloud Dataflow, you can also consider the following products

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

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

Microsoft Power BI - BI visualization and reporting for desktop, web or mobile

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

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.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?