Down only when probes on three continents agree. Prepaid credits, no seats, no tiers.
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Which is more popular?
Based on our record, Apache Kafka
seems to be a lot more popular than Embedly.
While we know about 159 links to Apache Kafka,
we've tracked only 13 mentions of Embedly.
social mentions
13 vs 159
Advertising popularity
100% vs 0%
alternatives listed
83 vs 209
Base details
Website, pricing, platforms and company facts side by side.
Ease of Use Embedly provides a simple API that allows developers to embed content from a wide variety of sources with minimal effort.
Content Versatility Supports embedding content from many major providers such as YouTube, Instagram, Twitter, and more, enhancing the versatility of web content.
Customization Offers customizable embed options so developers can tailor the appearance and behavior of the embedded content to fit their needs.
Aggregated Data Provides enriched metadata from embedded content, which could be useful for SEO and content analysis.
Cross-Platform Support Embeds are responsive and work well across different devices and platforms, providing a consistent user experience.
Possible disadvantages
Cost Embedly offers a freemium model, but the free tier has limitations, and the premium plans can be expensive for small businesses or individual developers.
Dependency Relying on a third-party service means developers are dependent on Embedly for uptime and performance, which could be a potential risk if the service experiences issues.
Privacy Concerns Using Embedly means sharing data with a third-party service, which could raise privacy concerns depending on the type of content being embedded.
Limitations in Custom Sources While Embedly supports many major providers, it may not support lesser-known or niche content sources, which could be a drawback for certain use cases.
API Rate Limits The API has rate limits even on premium plans, which could be restrictive for high-traffic websites or applications requiring extensive embedding.
High Throughput Kafka is capable of handling thousands of messages per second due to its distributed architecture, making it suitable for applications that require high throughput.
Scalability Kafka can easily scale horizontally by adding more brokers to a cluster, making it highly scalable to serve increased loads.
Fault Tolerance Kafka has built-in replication, ensuring that data is replicated across multiple brokers, providing fault tolerance and high availability.
Durability Kafka ensures data durability by writing data to disk, which can be replicated to other nodes, ensuring data is not lost even if a broker fails.
Real-time Processing Kafka supports real-time data streaming, enabling applications to process and react to data as it arrives.
Decoupling of Systems Kafka acts as a buffer and decouples the production and consumption of messages, allowing independent scaling and management of producers and consumers.
Wide Ecosystem The Kafka ecosystem includes various tools and connectors such as Kafka Streams, Kafka Connect, and KSQL, which enrich the functionality of Kafka.
Strong Community Support Kafka has strong community support and extensive documentation, making it easier for developers to find help and resources.
Possible disadvantages
Complex Setup and Management Kafka's distributed nature can make initial setup and ongoing management complex, requiring expert knowledge and significant administrative effort.
Operational Overhead Running Kafka clusters involves additional operational overhead, including hardware provisioning, monitoring, tuning, and scaling.
Latency Sensitivity Despite its high throughput, Kafka may experience increased latency in certain scenarios, especially when configured for high durability and consistency.
Learning Curve The concepts and architecture of Kafka can be difficult for new users to grasp, leading to a steep learning curve.
Hardware Intensive Kafka's performance characteristics often require dedicated and powerful hardware, which can be costly to procure and maintain.
Dependency Management Managing Kafka's dependencies and ensuring compatibility between versions of Kafka, Zookeeper, and other ecosystem tools can be challenging.
Limited Support for Small Messages Kafka is optimized for large throughput and can be inefficient for applications that require handling a lot of small messages, where overhead can become significant.
Operational Complexity for Small Teams Smaller teams might find the operational complexity and maintenance burden of Kafka difficult to manage without a dedicated operations or DevOps team.
Analysis
An editorial look at what each product does well and who it suits.
EmbedlyApache Kafka
Overall verdict
Embedly is generally considered a good option for content embedding due to its comprehensive API and ease of use.
Why this product is good
Embedly provides a robust platform that allows developers to easily embed multimedia content from a wide range of sources. The service simplifies the process of extracting and displaying content such as images, videos, and articles by providing a unified API. It supports a vast number of providers and offers customization options, making it a flexible tool for developers. Additionally, Embedly delivers content in a mobile-optimized way, ensuring a better user experience across different devices.
Recommended for
Developers looking to integrate multimedia content into websites or applications
Content creators and publishers who want to enrich their platforms with external content
Web and mobile app developers needing a simple solution for embedding content from multiple sources
Debezium is an open-source Change Data Capture (CDC) tool that originated from RedHat. It leverages Apache Kafka and Kafka Connect to enable real-time data replication from databases. Debezium was partly inspired by...
If you take the time to sort out the history of message queues, you will find a very interesting phenomenon. Most of the currently popular message queues were born around 2010. For example, Apache Kafka was born at...
Apache Kafka is a highly scalable and robust messaging queue system designed by LinkedIn and donated to the Apache Software Foundation. It's ideal for real-time data streaming and processing, providing high throughput...
Recommendations tracked on public social media and blogs since March 2021.
Embedly13 mentionsApache Kafka159 mentions
Automod remove videos less than 1second long?
You can see what kinds of properties you can see for media - I fed the URL of a video into embed.ly as that document suggested, but none of the fields returned gave me a video length... You may want to try with one of the images posted...
Source:
almost 3 years ago
Embedding videos on reddit
Some people report success with getting approved by https://embed.ly/, others report that service never responded to them.
Source:
over 3 years ago
Embed.ly — Provides APIs for embedding media in a webpage, responsive image scaling, extracting elements from a webpage. Free for up to 5,000 URLs/month at 15 requests/second.
- Source: dev.to
/
almost 4 years ago
The fix is an event exporter: a lightweight component that watches the Kubernetes event stream via the API server and forwards events to external destinations (sinks) like Elasticsearch, Slack, Loki, Kafka, or webhooks.
- Source: dev.to
/
about 2 months ago
Going Event-Driven? Read the Bill First.
Event-driven architecture fixes it by deleting the waiting. Service A publishes an event (say, "Order Placed") to a broker like Kafka or Amazon EventBridge. Whoever cares about that event picks it up and reacts in their own time. Service...
- Source: dev.to
/
23 days ago
Provision managed resources (Postgres, MongoDB, Kafka, RabbitMQ, etc.) from DigitalOcean, Supabase, Scaleway, AWS, or Google Cloud. It doesn't really matter which; they all offer good SLAs.
- Source: dev.to
/
about 1 month ago
StatCounter is a simple but powerful real-time web analytics service that helps you track, analyse and understand your visitors so you can make good decisions to become more successful online.
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