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Infoworks eliminates big data complexity by automating data engineering through the company’s Autonomous Data Engine, which has been adopted by some of the largest enterprises in the world. Using a code-free environment, Infoworks allows organizations to quickly create and manage data use cases from source to consumption. Customers deploy projects to production within days, dramatically increasing analytics agility and time to value.
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Based on our record, Apache Kafka seems to be a lot more popular than Infoworks.io. While we know about 120 links to Apache Kafka, we've tracked only 4 mentions of Infoworks.io. 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.
You should check out infoworks.io - they have this concept of domains which can restrict data sets and the users that can do any transformations on it. They have a full airflow based visual orchestration engine as well as scheduler, transformation engine, ingestion, cataloging, etc. It's an end to end unified data engineering product. Source: over 2 years ago
For a simpler no-code visual config-driven (data ingest+ ELT+ airflow-based orchestration), all in a single unified platform, you may consider infoworks.io. It will even auto create a metadata catalog for you and give you lineage, audit capabilities. Source: almost 3 years ago
As long as you're truly after a lo/no-code solution that can automate your data onboarding (beyond ingestion), you'd be amiss to not try infoworks.io. Source: almost 3 years ago
I'm alerted to another vendor, infoworks.io, that offers a unified data engineering solution. I took their free personal testdrive. I learned that they have large number of source connectors (I think I read 200+), Spark based transformation engine, and visual workflow based on airflow. Source: almost 3 years ago
In today’s fast-paced digital landscape, effective data management and analysis are essential for businesses aiming to stay ahead of the curve. Fortunately, modern tools like Apache Kafka and RudderStack have revolutionized the way we handle and derive insights from large datasets. In this blog post, we’ll explore our experience implementing the Kafka Sink Connector to facilitate seamless event data transfer to... - Source: dev.to / about 1 month ago
Stream-processing platforms such as Apache Kafka, Apache Pulsar, or Redpanda are specifically engineered to foster event-driven communication in a distributed system and they can be a great choice for developing loosely coupled applications. Stream processing platforms analyze data in motion, offering near-zero latency advantages. For example, consider an alert system for monitoring factory equipment. If a... - Source: dev.to / 2 months ago
Apache Kafka is a distributed streaming platform capable of handling high throughput of data, while ReductStore is a databases for unstructured data optimized for storing and querying along time. - Source: dev.to / 3 months ago
*Push data *(original source image, GPS, timestamp) in a common place (Apache Kafka,...). - Source: dev.to / 3 months ago
RabbitMQ comes with administrative tools to manage user permissions and broker security and is perfect for low latency message delivery and complex routing. In comparison, Apache Kafka architecture provides secure event streams with Transport Layer Security(TLS) and is best suited for big data use cases requiring the best throughput. - Source: dev.to / 3 months ago
Airbyte - Replicate data in minutes with prebuilt & custom connectors
RabbitMQ - RabbitMQ is an open source message broker software.
Meltano - Open source data dashboarding
Apache ActiveMQ - Apache ActiveMQ is an open source messaging and integration patterns server.
Singer - Simple, Composable, Open Source ETL
Amazon SQS - Amazon Simple Queue Service is a fully managed message queuing service.