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StreamSets Data Collector VS Confluent

Compare StreamSets Data Collector VS Confluent and see what are their differences

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StreamSets Data Collector logo StreamSets Data Collector

The StreamSets Data Collector (SDC) is used to build, test and execute dataflow pipelines for data lake and multi-cloud data movement plus cybersecurity, IoT and customer 360 applications.

Confluent logo Confluent

Confluent offers a real-time data platform built around Apache Kafka.
  • StreamSets Data Collector Landing page
    Landing page //
    2023-10-20
  • Confluent Landing page
    Landing page //
    2023-10-22

StreamSets Data Collector features and specs

No features have been listed yet.

Confluent features and specs

  • Scalability
    Confluent is built on Apache Kafka, which allows for smooth scalability to handle growing data needs without significant performance degradation.
  • Real-Time Data Processing
    Confluent enables real-time streaming data processing, which is beneficial for applications requiring immediate data insights and actions.
  • Comprehensive Ecosystem
    Confluent provides a rich set of tools and connectors that integrate seamlessly with various data sources and sinks, making it easier to build and manage data pipelines.
  • Ease of Use
    Confluent offers an intuitive user interface and comprehensive documentation, which simplifies the setup and management of Kafka clusters.
  • Managed Service Option
    Confluent Cloud provides a fully managed Kafka service, reducing the operational burden on the engineering team and allowing businesses to focus on developing applications.
  • Advanced Security Features
    Confluent offers robust security features including encryption, SSL, ACLs, and more, ensuring that data streams are protected.
  • Strong Customer Support
    Confluent offers professional support and consultancy services which can be very helpful for enterprises requiring 24/7 support and expertise.

Possible disadvantages of Confluent

  • Cost
    Confluent can be expensive, especially for small to medium-sized businesses. The costs can grow significantly with scale and additional enterprise features.
  • Complexity
    Despite its ease of use, the underlying system’s complexity can pose a challenge, particularly for teams who are new to Kafka or streaming data technologies.
  • Resource Intensive
    Running Confluent on-premises can be resource-intensive, requiring significant computational and storage resources to maintain optimal performance.
  • Learning Curve
    For those unfamiliar with Kafka and streaming technologies, there is a steep learning curve which can lead to longer implementation times.
  • Vendor Lock-In
    Utilizing Confluent’s proprietary tools and connectors can result in vendor lock-in, making it difficult to switch to alternative solutions without considerable effort and reconfiguration.
  • Dependency on Cloud Provider
    If using Confluent Cloud, dependency on the cloud provider’s infrastructure may introduce compliance and control limitations, particularly for businesses with strict data sovereignty requirements.

StreamSets Data Collector videos

+ Add

Data Pipeline Preview with StreamSets Data Collector

Confluent videos

+ Add

1. Intro | Monitoring Kafka in Confluent Control Center

More videos:

  • Review - Jason Gustafson, Confluent: Revisiting Exactly One Semantics (EOS) | Bay Area Apache Kafka® Meetup
  • Review - CLEARER SKIN AFTER 1 USE‼️| Ancient Cosmetics Update✨| CONFLUENT & RETICULATED PAPILLOMATOSIS CURE?😩

Category Popularity

0-100% (relative to StreamSets Data Collector and Confluent)

StreamSets Data Collector

Confluent

Data Management
20 20%
Data Management
80% 80
Stream Processing
16 16%
Stream Processing
84% 84
Big Data
16 16%
Big Data
84% 84
Tool
100 100%
Tool
0% 0

User comments

Share your experience with using StreamSets Data Collector and Confluent. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Confluent seems to be more popular. It has been mentiond 1 time 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.

StreamSets Data Collector mentions (0)

We have not tracked any mentions of StreamSets Data Collector yet. Tracking of StreamSets Data Collector recommendations started around Mar 2021.

Confluent mentions (1)

  • Spring Boot Event Streaming with Kafka
    We’re going to setup a Kafka cluster using confluent.io, create a producer and consumer as well as enhance our behavior driven tests to include the new interface. We’re going to update our helm chart so that the updates are seamless to Kubernetes and we’re going to leverage our observability stack to propagate the traces in the published messages. Source: about 3 years ago

What are some alternatives?

When comparing StreamSets Data Collector and Confluent, you can also consider the following products

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.

Spark Streaming - Spark Streaming makes it easy to build scalable and fault-tolerant streaming applications.

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

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

PieSync - Seamless two-way sync between your CRM, marketing apps and Google in no time

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