Software Alternatives & Reviews

Apache Storm VS Striim

Compare Apache Storm VS Striim and see what are their differences

Apache Storm logo Apache Storm

Apache Storm is a free and open source distributed realtime computation system.

Striim logo Striim

Striim provides an end-to-end, real-time data integration and streaming analytics platform.
  • Apache Storm Landing page
    Landing page //
    2019-03-11
  • Striim Landing page
    Landing page //
    2023-10-20

Apache Storm videos

Apache Storm Tutorial For Beginners | Apache Storm Training | Apache Storm Example | Edureka

More videos:

  • Review - Developing Java Streaming Applications with Apache Storm
  • Review - Atom Text Editor Option - Real-Time Analytics with Apache Storm

Striim videos

Striim On Premise to Azure Integration Step 1

More videos:

  • Review - Tech review: AwoX Striim LED Light Bulb
  • Review - Striim On Premise to Azure Integration Step 2

Category Popularity

0-100% (relative to Apache Storm and Striim)
Big Data
100 100%
0% 0
Development
0 0%
100% 100
Databases
100 100%
0% 0
Backup & Sync
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Storm and Striim

Apache Storm Reviews

Top 15 Kafka Alternatives Popular In 2021
Apache Storm is a recognized, distributed, open-source real-time computational system. It is free, simple to use, and helps in easily and accurately processing multiple data streams in real-time. Because of its simplicity, it can be utilized with any programming language and that is one reason it is a developer’s preferred choice. It is fast, scalable, and integrates well...
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Storm is an open-source distributed real-time computational system for processing data streams. Similar to what Hadoop does for batch processing, Apache Storm does for unbounded streams of data in a reliable manner. Built by Twitter, Apache Storm specifically aims at the transformation of data streams. Storm has many use cases like real-time analytics, online machine...

Striim Reviews

Top 14 ETL Tools for 2023
Striim offers a real-time data integration platform for big data workloads. Users can integrate a wide variety of data sources and targets — including Oracle, SQL Server, MySQL, PostgreSQL, MongoDB, and Hadoop — in various file formats. Striim is compliant with data privacy regulations such as GDPR and HIPAA, and users can define pre-load transformations using SQL or Java.
Top 7 ETL Tools for 2021
Striim offers a real-time data integration platform for big data workloads. Users can integrate a wide variety of data sources and targets in roughly 20 different file formats, including Oracle, SQL Server, MySQL, PostgreSQL, MongoDB, and Hadoop. Striim is compliant with data privacy regulations such as GDPR and HIPAA, and users can define pre-load transformations using SQL...
Source: www.xplenty.com
The 28 Best Data Integration Tools and Software for 2020
Description: Striim offers a real-time data integration solution that enables continuous query processing and streaming analytics. Striim integrates data from a wide variety of sources, including transaction/change data, events, log files, application and IoT sensor, and real-time correlation across multiple streams. The platform features pre-built data pipelines,...

Social recommendations and mentions

Based on our record, Apache Storm seems to be more popular. It has been mentiond 11 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.

Apache Storm mentions (11)

  • Data Engineering and DataOps: A Beginner's Guide to Building Data Solutions and Solving Real-World Challenges
    There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 1 year ago
  • Real Time Data Infra Stack
    Although this article lists a lot of targets for technical selection, there are definitely others that I haven't listed, which may be either outdated, less-used options such as Apache Storm or out of my radar from the beginning, like JAVA ecosystem. - Source: dev.to / over 1 year ago
  • In One Minute : Hadoop
    Storm, a system for real-time and stream processing. - Source: dev.to / over 1 year ago
  • Elon Musk reportedly wants to fire 75% of Twitter’s employees
    Google has scaled well and has helped others scale, Twitter has always been behind by years. I think the only thing they did well was Twitter Storm, now taken up by Apache Foundation. Source: over 1 year ago
  • Spark for beginners - and you
    Streaming: Sparks Streamings's latency is at least 500ms, since it operates on micro-batches of records, instead of processing one record at a time. Native streaming tools like Storm, Apex or Flink might be better for low-latency applications. - Source: dev.to / over 2 years ago
View more

Striim mentions (0)

We have not tracked any mentions of Striim yet. Tracking of Striim recommendations started around Mar 2021.

What are some alternatives?

When comparing Apache Storm and Striim, you can also consider the following products

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

HVR - Your data. Where you need it. HVR is the leading independent real-time data replication solution that offers efficient data integration for cloud and more.

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

Oracle Data Integrator - Oracle Data Integrator is a data integration platform that covers batch loads, to trickle-feed integration processes.

Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

Bryteflow Data Replication and Integration - Bryteflow is a popular platform that offers many services, including data replication and integration.