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Cohesity VS Apache Flink

Compare Cohesity VS Apache Flink and see what are their differences

Cohesity logo Cohesity

Cohesity brings together fractured secondary data sources into a single platform, helping companies store, protect, and learn from their data instantly.

Apache Flink logo Apache Flink

Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
  • Cohesity Landing page
    Landing page //
    2023-09-27
  • Apache Flink Landing page
    Landing page //
    2023-10-03

Cohesity

$ Details
-
Release Date
2013 January
Startup details
Country
United States
State
California
City
San Jose
Founder(s)
Mohit Aron
Employees
1,000 - 1,999

Cohesity videos

2-minute: Cohesity Data Protection Overview

More videos:

  • Review - Cohesity vs. Legacy Solutions
  • Review - Cohesity Comprehensive Data Protection and Compliance

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 Cohesity and Apache Flink)
Cloud Storage
100 100%
0% 0
Big Data
0 0%
100% 100
Backup And Disaster Recovery
Stream Processing
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 Cohesity and Apache Flink

Cohesity Reviews

15 Best Acronis Alternatives 2022
Cohesity consolidates all of your disparate systems into a single, unified web-scale platform by using Cohesity.

Apache Flink Reviews

We have no reviews of Apache Flink yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Apache Flink seems to be a lot more popular than Cohesity. While we know about 30 links to Apache Flink, we've tracked only 1 mention of Cohesity. 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.

Cohesity mentions (1)

  • Cohesity harassment
    Cohesity has been calling me for weeks now (and twice in the past hour) asking me to sign up for a webinar. I've had enough, and I've blocked cohesity.com from emailing anyone at my company. Source: almost 3 years ago

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 / 4 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 / 24 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 Cohesity and Apache Flink, you can also consider the following products

Veeam - Veeam develops backup, disaster recovery and virtualization management software for VMware and Hyper-V virtual environments.

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

Rubrik - Rubrik delivers instant application availability for recovery, search, cloud, and development.

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

Druva - Druva is a converged data protection solution offering data center class availability and governance for the mobile workforce.

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