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Life & fun · alternatives · 2026

BR

Spark Streamliner is a tool for building real-time data pipelines using Apache Spark. It enables developers and data engineers to process streaming data efficiently. The product launched in 2015 and helps organizations… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Build Real-Time Data Pipelines with Spark Streamliner launched in 2015; newer entries below may have overtaken it.

  1. 1

    A single DataOps platform for data engineering

    2021 · ibm.com · its alternatives →

  2. 2

    The .NET web framework for makers

    2023 · its alternatives →

  3. 3
    LLM Spark▲365

    Dev platform for building production ready LLM apps

    2023 · yourgpt.ai · its alternatives →

  4. 4

    Next-gen massive data integration framework

    2022 · seatunnel.apache.org · its alternatives →

  5. 5LV
  6. 6

    Connect your data, where you want it, in milliseconds

    2023 · estuary.dev · its alternatives →

  7. 7

    No-code platform to monitor and visualize IoT real-time data

    2021 · cedalo.com · its alternatives →

  8. 8
    Streamdal▲143

    Detect and resolve data quality incidents faster

    2023 · streamdal.com · its alternatives →

  9. 9
    Hivel▲192

    Build High Velocity teams

    2022 · hivel.ai · its alternatives →

  10. 10

    Every data pipeline job I had to tackle required quite a few components to set up: - One tool to ingest data - Another one to transform it - If you wanted to run Python, set up an orchestrator - If you need to check the data, a data quality tool Let alone this being hard to set up and taking time, it is also pretty high-maintenance. I had to do a lot of infra work, and while this being billable hours for me I didn’t enjoy the work at all. For some parts of it, there were nice solutions like dbt, but in the end for an end-to-end workflow, it didn’t work. That’s why I decided to build an…

    2024 · github.com · its alternatives →

  11. 11LB

    Hey HN, Spark event logs run into 100s of MBs and offer a wealth of insight into your workloads but making sense of them has always been quite a bit prohibitive. We’ve recently built a lightweight tool that automatically parses Spark event logs and surfaces targeted insights to help you optimize your data jobs. Whether you’re chasing down a bottleneck or balancing performance vs. cost, the profiler got you covered with real-time configuration recommendations, data skew analysis, and more. Curious how it works in action? Check out this quick Loom video for a walk-through:…

    2025 · datasre.ai · its alternatives →

  12. 12

    Managed RAG pipelines, made easy

    2025 · blog.cloudflare.com · its alternatives →

  13. 13
    IOMETE▲85

    The First Cloud-Prem Data Lakehouse

    2023 · iomete.com · its alternatives →

  14. 14

    Create and manage full-stack micro-apps with AI prompts

    2024 · githubnext.com · its alternatives →

  15. 15
    Spark▲85

    Build internet-connected hardware.

    2014 · particle.io · its alternatives →

  16. 16WT
  17. 17RT

    We are working on a product which makes stream processing easy for data analysts and data scientists. It’s a higher level alternative to Flink, Kafka Streams and Spark Streams. As well as making stream processing simpler, we also felt that lots of people were building these AWS stream processing platforms based on Kafka and something like Flink so wanted to offer this as a service. We would welcome any input on the space or approach: Home page: http://Timeflow.systems Demo: https://youtu.be/fGfgBaHXOkE

    2020 · its alternatives →

  18. 18

    Hey HN! We are building *open source infrastructure for deploying customer-facing data pipelines.* Here’s our repo https://github.com/pipebird/pipebird and website https://pipebird.com/. Pipebird (YC W22) is designed to enable companies that generate important data to offer secure data pushes to their customers’ warehouses, directly from their products. Our team was previously building in fintech, where we heard from many of our peers that their customers wanted data pushed directly to their warehouses. Customers wanted to bring data into their source of…

    2022 · github.com · its alternatives →

  19. 19

    Hello Everyone! We built SQLFlow as a lightweight stream processing engine. We leverage DuckDB as the stream processing engine, which gives SQLFlow the ability to process 10's of thousands of messages a second using ~250MiB of memory! DuckDB also supports a rich ecosystem of sinks and connectors! https://sql-flow.com/docs/category/tutorials/ https://github.com/turbolytics/sql-flow We were tired of running JVM's for simple stream processing, and also of bespoke one off stream processors I would love your feedback, criticisms and/or…

    Dec 2025 · sql-flow.com · its alternatives →

  20. 20

    Realtime analytics database

    2014 · its alternatives →

  21. 21

    Unify MLOps. Accelerate AI. Gain open-source control.

    2025 · github.com · its alternatives →

  22. 22SI
  23. 23

    Simplify big data and AI

    2018 · databricks.com · its alternatives →

  24. 24

    Build ETL pipelines step-by-step via a simple no-code UI.

    2020 · datapipelines.com · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →