Software Alternatives, Accelerators & Startups

Tranztec VS Apache Flink

Compare Tranztec VS Apache Flink and see what are their differences

Tranztec logo Tranztec

Integrations for every part of the Trucking Logistics Industry Tranzactor is the the industry standard for integrations with Mobilecomm, 3rd Part Mobile Applications and yesterdays and todays most popular TMS systems.

Apache Flink logo Apache Flink

Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
  • Tranztec Landing page
    Landing page //
    2023-10-08
  • Apache Flink Landing page
    Landing page //
    2023-10-03

Tranztec videos

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Apache Flink videos

GOTO 2019 • Introduction to Stateful Stream Processing with Apache Flink • Robert Metzger

More videos:

  • Tutorial - Apache Flink Tutorial | Flink vs Spark | Real Time Analytics Using Flink | Apache Flink Training
  • Tutorial - How to build a modern stream processor: The science behind Apache Flink - Stefan Richter

Category Popularity

0-100% (relative to Tranztec and Apache Flink)
File Manager
100 100%
0% 0
Big Data
0 0%
100% 100
Mac File Manager
100 100%
0% 0
Stream Processing
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Apache Flink seems to be more popular. It has been mentiond 30 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.

Tranztec mentions (0)

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

Apache Flink mentions (30)

  • Show HN: Restate, low-latency durable workflows for JavaScript/Java, in Rust
    Restate is built as a sharded replicated state machine similar to how TiKV (https://tikv.org/), Kudu (https://kudu.apache.org/kudu.pdf) or CockroachDB (https://github.com/cockroachdb/cockroach) since it makes it possible to tune the system more easily for different deployment scenarios (on-prem, cloud, cost-effective blob storage). Moreover, it allows for some other cool things like seamlessly moving from one log... - Source: Hacker News / 3 days ago
  • Array Expansion in Flink SQL
    I’ve recently started my journey with Apache Flink. As I learn certain concepts, I’d like to share them. One such "learning" is the expansion of array type columns in Flink SQL. Having used ksqlDB in a previous life, I was looking for functionality similar to the EXPLODE function to "flatten" a collection type column into a row per element of the collection. Because Flink SQL is ANSI compliant, it’s no surprise... - Source: dev.to / 23 days ago
  • Show HN: An SQS Alternative on Postgres
    You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / about 1 month ago
  • Top 10 Common Data Engineers and Scientists Pain Points in 2024
    Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / 2 months ago
  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 4 months ago
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What are some alternatives?

When comparing Tranztec and Apache Flink, you can also consider the following products

Business Integration Suite - Digital Change impacts companies to constantly design and implement new digital business models. Seamless integration and collaboration of all stakeholder is key for a healthy digital ecosystem.

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

EXIM EDI - Want to level up your business? Look no further than our website & marketing solutions, websites, product visualization, catalog data and EDI. 

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

Infocon Systems - Cloud Based EDI exchange for Any Trading Partner, Any Industry and Any Integration.

Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.