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StreamSets VS RisingWave

Compare StreamSets VS RisingWave and see what are their differences

JackHamr
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Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

StreamSets logo StreamSets

StreamSets provides Continuous Ingest technology for the next generation of big data applications.

RisingWave logo RisingWave

RisingWave is a stream processing platform that utilizes SQL to enhance data analysis, offering improved insights on real-time data.
  • StreamSets Landing page
    Landing page //
    2023-09-13
  • RisingWave Landing page
    Landing page //
    2023-08-29

StreamSets features and specs

  • User-Friendly Interface
    StreamSets provides an intuitive and visually appealing interface for designing and managing data pipelines, making it accessible even for users without extensive coding experience.
  • Real-Time Data Processing
    The platform excels at real-time data ingestion, transformation, and delivery, enabling timely insights and immediate actions on streaming data.
  • Comprehensive Connectors
    StreamSets supports a wide range of data sources and destinations out of the box, including cloud services, databases, and big data platforms, ensuring versatility in data integration tasks.
  • Data Drift Management
    It offers robust features for detecting and managing data drift, helping maintain data quality and consistency over time as source schemas evolve.
  • Scalability
    StreamSets is designed to scale effortlessly with increasing data volumes and can handle large-scale data pipelines efficiently.

Possible disadvantages of StreamSets

  • Cost
    The pricing model can be expensive, particularly for small to mid-sized enterprises, making it less accessible for organizations with limited budgets.
  • Learning Curve
    Although the interface is user-friendly, mastering the platform's advanced features and configurations may require a significant learning curve.
  • Resource Intensive
    Running StreamSets can be resource-intensive, requiring substantial computational and memory resources, which may lead to higher operational costs.
  • Limited Custom Scripting
    While StreamSets offers many in-built functionalities, it provides limited scope for custom scripting compared to other data pipeline tools, which may restrict flexibility for complex custom tasks.
  • Dependency on Internet Connectivity
    For cloud-based deployments, the performance and reliability of StreamSets can be heavily dependent on internet connectivity, which could be a concern for organizations with unstable connections.

RisingWave features and specs

No features have been listed yet.

Analysis of StreamSets

Overall verdict

  • Yes, StreamSets is considered to be a good option for organizations seeking a comprehensive data integration and pipeline management solution. Its ability to support complex data workflows and provide detailed insights into data processing makes it a valuable tool for data engineers and IT operations teams.

Why this product is good

  • StreamSets is regarded positively due to its user-friendly interface and robust data integration features. It supports a wide range of data sources, providing flexibility for diverse data workflows. The platform is designed to handle both batch and streaming data, which is essential for organizations looking to manage real-time data processing and automation effectively. Additionally, StreamSets offers strong data observability features, which help in monitoring and optimizing data pipelines.

Recommended for

  • Organizations that require both batch and real-time data processing
  • Data engineers seeking a versatile and intuitive pipeline management tool
  • Companies looking to improve data observability and pipeline monitoring
  • Businesses with diverse data sources that need seamless integration

StreamSets videos

+ Add

What is StreamSets Transformer?

More videos:

  • Review - Making Apache Kafka Dead Easy With StreamSets | DZone.com Webinar
  • Review - Power Your Delta Lake with Streaming Transactional Changes - Rupal Shah (StreamSets)

RisingWave videos

+ Add

RisingWave: Reinventing(?!) Stream Processing in the Cloud Era (Yingjun Wu)

More videos:

  • Review - Building Cost Effective Stream Processing Applications with RisingWave and Pulsar
  • Review - RISINGWAVE REBOOT

Category Popularity

0-100% (relative to StreamSets and RisingWave)

StreamSets

RisingWave

DevOps Tools
100 100%
DevOps Tools
0% 0
Databases
0 0%
Databases
100% 100
Continuous Integration And Delivery
100 100%
Continuous Integration And Delivery
0% 0
Stream Processing
45 45%
Stream Processing
55% 55

User comments

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

Based on our record, RisingWave should be more popular than StreamSets. It has been mentiond 18 times 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 mentions (2)

  • Best way to automate JSON to CSV/Relational Tables at scale? Anyone have used Flexter?
    If you would like to take a look at https://streamsets.com/ the Data Collector product can handle this for you as well as dynamically generate the target tables. It has a number of functions to handle your JSON no matter the complexity. However, given the dynamic nature it may benefit to touch base so please feel free to chat or message me. Source: about 4 years ago
  • Data engineering in reality
    StreamSets offers a free tier and free option for training. You can build, run, and manage your pipelines in one place. Source: over 4 years ago

RisingWave mentions (18)

  • Build a Real-Time Gaming Analytics Pipeline with Justย SQL
    Player data is ingested into a Kafka topic, and RisingWave consumes this stream to create materialized views for real-time analysis. Using BI tools like Superset or Grafana, weโ€™ll build dashboards to monitor player performance and power leaderboards. Finally, Iโ€™ll show how the results from RisingWave can be sent to analytics platforms like BigQuery, Snowflake, or StarRocks and ML models for downstream applications... - Source: dev.to / 10 months ago
  • The Equality Delete Problem in Apache Iceberg
    RisingWave is the only system today that supports complete, end-to-end architecture for streaming CDC into Apache Iceberg, making it the state-of-the-art solution in this space. - Source: dev.to / 11 months ago
  • Towards Sub-100ms Latency Stream Processing with an S3-Based Architecture
    RisingWave is a high-performance streaming database built in Rust. Itโ€™s PostgreSQL-compatible and lets users write sophisticated stream processing logic using standard SQL - no need to learn a new DSL or framework. - Source: dev.to / about 1 year ago
  • Unlock the Power of Realโ€‘Time HubSpot CRM Automation
    We're excited to announce that now you can: by integrating HubSpot webhooks directly with RisingWave. This powerful connection allows you to stream your CRM, marketing, and sales data from HubSpot into our unified data platform for true real-time processing, analysis, and automation. - Source: dev.to / about 1 year ago
  • Introducing RisingWave's Hosted Iceberg Catalog-No External Setup Needed
    At RisingWave, our goal is to simplify the process of building real-time data applications. A key part of this is enabling users to build modern, open data architectures. Thatโ€™s why we developed the Iceberg Table Engine (see the Iceberg table engine docs), which allows you to stream data directly into tables using the open Apache Iceberg format. This is a powerful way to build a streaming lakehouse where your data... - Source: dev.to / about 1 year ago
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What are some alternatives?

When comparing StreamSets and RisingWave, you can also consider the following products

Puppet Enterprise - Get started with Puppet Enterprise, or upgrade or expand.

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

Terraform - Tool for building, changing, and versioning infrastructure safely and efficiently.

Materialize - A Streaming Database for Real-Time Applications

Packer - Packer is an open-source software for creating identical machine images from a single source configuration.

Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.

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