Notes, tasks, passwords, journal, files, calendar, contacts and bookmarks, with mood and medication tracking. Encrypted on your device. Open source, no ads, no trackers. Free forever; Pro is a one-time purchase.
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Which is more popular?
Based on our record, Obsidian
seems to be a lot more popular than Google Cloud Dataflow.
While we know about 1532 links to Obsidian,
we've tracked only 14 mentions of Google Cloud Dataflow.
social mentions
1,532 vs 14
Note Taking popularity
100% vs 0%
alternatives listed
240+ vs 147
Base details
Website, pricing, platforms and company facts side by side.
Local-first Obsidian stores your notes locally on your device, giving you full control over your data and enhancing privacy.
Markdown Support Obsidian uses Markdown, making it easy to format text and compatible with many other text editors and tools.
Bidirectional Linking You can create bidirectional links between notes, which helps in building a knowledge graph and navigating related information more easily.
Customizability Obsidian is highly customizable with community plugins, themes, and various settings to fit different workflows.
Graph View Provides a visual graph view of your notes and their connections, aiding in understanding relationships and discovering insights.
Offline Access Since the notes are stored locally, you can access and edit them without an internet connection.
Possible disadvantages
Learning Curve Obsidian can be complex and overwhelming for beginners due to its extensive features and customizable nature.
Sync Limitations While local-first is great for privacy, it requires additional steps or third-party solutions for syncing across devices.
No True Real-time Collaboration Obsidian lacks native real-time collaboration features, making it less suitable for collaborative work compared to cloud-based solutions.
Limited Mobile Features The mobile version of Obsidian, while functional, is not as robust as the desktop application, potentially hindering productivity on the go.
Dependence on Plugins Many advanced features require the use of third-party plugins, which could lead to compatibility issues and reliance on community support.
Performance on Large Vaults Performance might degrade with a very large number of notes or complex graphs, impacting usability.
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
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.
Analysis
An editorial look at what each product does well and who it suits.
ObsidianGoogle Cloud Dataflow
Overall verdict
Overall, Obsidian.md is an excellent tool for users looking for a versatile and powerful note-taking application. Its unique features such as backlinking, markdown support, and robust customization options make it a favorite among knowledge management enthusiasts.
Why this product is good
Obsidian.md is considered good by many users because it is a powerful knowledge management and note-taking application that leverages Markdown for document formatting. It allows for bi-directional linking between notes, which helps in creating a network of interconnected ideas, often described as a 'second brain.' Its ability to support plugins, themes, and robust graph visualization also adds to its appeal. Additionally, it stores notes locally, ensuring privacy and data ownership, while being cross-platform compatible across Windows, macOS, and Linux.
Recommended for
Knowledge workers who need a powerful tool to organize and connect their thoughts.
Students who are looking to create a structured and visually interconnected note system.
Writers and researchers who benefit from linking related ideas and maintaining detailed notes.
Tech-savvy users or developers who appreciate the local storage and open ecosystem for plugins and customization.
Overall verdict
Google Cloud Dataflow is a strong choice for users who need a flexible and scalable data processing solution. It is particularly well-suited for real-time and large-scale data processing tasks. However, the best choice ultimately depends on your specific requirements, including cost considerations, existing infrastructure, and technical skills.
Why this product is good
Google Cloud Dataflow is a fully managed service for stream and batch data processing. It is based on the Apache Beam model, allowing for a unified data processing approach. It is highly scalable, offers robust integration with other Google Cloud services, and provides powerful data processing capabilities. Its serverless nature means that users do not have to worry about infrastructure management, and it dynamically allocates resources based on the data processing needs.
Recommended for
Organizations that require real-time data processing.
Projects involving complex data transformations.
Users who already utilize Google Cloud Platform and need seamless integration with other Google services.
Developers and data engineers familiar with Apache Beam or those willing to learn.
One thing to note: Notion bills itself as an Evernote competitor for personal users. It can be—but it's too much for most people, and its offline functionality isn't the best. If you love the idea of Notion, go right...
This app is the kind of thing that, if you’re into it, will have you exploring its various ins, outs, and add-ons for days and weeks on end. Obsidian uses the Markdown format for its notes (which means they can be...
However, it's important to note that Obsidian's whiteboard functionality is not as robust as dedicated collaboration tools. While it lacks real-time basic collaboration features, Obsidian compensates with its vibrant...
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...
Social recommendations and mentions
Recommendations tracked on public social media and blogs since March 2021.
The reasons live somewhere else: in practice notes in an Obsidian vault, one note per convention, with the repos it has held in. A note starts as an idea, moves to trialing, and only becomes enforced once I've applied it again in a few...
- Source: dev.to
/
2 days ago
It's the team version of the second brain you build with Obsidian and Claude.
- Source: dev.to
/
6 days ago
Mine and yours first Obsidian plugin
The first time I downloaded Obsidian was about two years ago and I really liked the concept of storing everything locally in simple markdown files without unnecessary clutter.
- Source: dev.to
/
5 days ago
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...
Source:
almost 4 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:
about 4 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:
about 4 years ago
Joplin is a free, open source note taking and to-do application, which can handle a large number of notes organised into notebooks. The notes are searchable, tagged and modified either from the applications directly or from your own text editor.
Compare Joplin to Obsidian or Google Cloud Dataflow:
Notion
Logseq
Joplin
Evernote
Roam Research
Bear
Typora
Amazon EMR
Google BigQuery
Qubole
Snowflake
Databricks
Apache Beam
Amazon Kinesis
