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Apache Flink VS Sumo Logic

Compare Apache Flink VS Sumo Logic and see what are their differences

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Apache Flink logo Apache Flink

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

Sumo Logic logo Sumo Logic

Sumo Logic is a secure, purpose-built cloud-based machine data analytics service that leverages big data for real-time IT insights
  • Apache Flink Landing page
    Landing page //
    2023-10-03
  • Sumo Logic Landing page
    Landing page //
    2023-10-20

Apache Flink features and specs

  • Real-time Stream Processing
    Apache Flink is designed for real-time data streaming, offering low-latency processing capabilities that are essential for applications requiring immediate data insights.
  • Event Time Processing
    Flink supports event time processing, which allows it to handle out-of-order events effectively and provide accurate results based on the time events actually occurred rather than when they were processed.
  • State Management
    Flink provides robust state management features, making it easier to maintain and query state across distributed nodes, which is crucial for managing long-running applications.
  • Fault Tolerance
    The framework includes built-in mechanisms for fault tolerance, such as consistent checkpoints and savepoints, ensuring high reliability and data consistency even in the case of failures.
  • Scalability
    Apache Flink is highly scalable, capable of handling both batch and stream processing workloads across a distributed cluster, making it suitable for large-scale data processing tasks.
  • Rich Ecosystem
    Flink has a rich set of APIs and integrations with other big data tools, such as Apache Kafka, Apache Hadoop, and Apache Cassandra, enhancing its versatility and ease of integration into existing data pipelines.

Possible disadvantages of Apache Flink

  • Complexity
    Flink’s advanced features and capabilities come with a steep learning curve, making it more challenging to set up and use compared to simpler stream processing frameworks.
  • Resource Intensive
    The framework can be resource-intensive, requiring substantial memory and CPU resources for optimal performance, which might be a concern for smaller setups or cost-sensitive environments.
  • Community Support
    While growing, the community around Apache Flink is not as large or mature as some other big data frameworks like Apache Spark, potentially limiting the availability of community-contributed resources and support.
  • Ecosystem Maturity
    Despite its integrations, the Flink ecosystem is still maturing, and certain tools and plugins may not be as developed or stable as those available for more established frameworks.
  • Operational Overhead
    Running and maintaining a Flink cluster can involve significant operational overhead, including monitoring, scaling, and troubleshooting, which might require a dedicated team or additional expertise.

Sumo Logic features and specs

  • Scalability
    Sumo Logic is designed to handle large volumes of data, making it suitable for organizations of different sizes and industries. It can scale up or down based on your needs.
  • Real-time Analytics
    The platform provides real-time analysis of logs and metrics, allowing for immediate insights and faster decision-making.
  • Unified Platform
    Sumo Logic offers a single platform for application observability, security, and compliance, reducing the need for multiple tools and streamlining workflows.
  • Machine Learning Capabilities
    The platform includes advanced machine learning features for anomaly detection, predictive analytics, and root cause analysis, enhancing the ability to detect and troubleshoot issues.
  • Integrations
    Sumo Logic supports numerous integrations with other tools and platforms, including AWS, Azure, Google Cloud, and various DevOps, security, and observability tools.
  • Compliance and Security
    The platform offers robust security features and facilitates compliance with various industry standards, such as HIPAA, GDPR, and SOC 2.

Possible disadvantages of Sumo Logic

  • Cost
    Sumo Logic can be expensive, particularly for smaller organizations or those with budget constraints. The cost may increase significantly with higher data volumes.
  • Complexity
    The platform has a steep learning curve, especially for users who are new to log management and analytics tools. This could lead to a longer onboarding process.
  • Search Performance
    In some cases, users have reported slow search performance, especially when querying large datasets or during peak usage times.
  • Limited Customization
    While Sumo Logic offers a wide range of features, there are limitations in customizing dashboards and alerts to fit specific requirements fully.
  • Dependence on Internet Connectivity
    As a cloud-based solution, Sumo Logic requires a reliable internet connection. Any disruption in connectivity can impact access to the platform and its features.

Analysis of Apache Flink

Overall verdict

  • Yes, Apache Flink is considered a good distributed stream processing framework.

Why this product is good

  • Rich api
    Flink offers a rich set of APIs for various levels of abstraction, catering to different needs of developers.
  • Scalability
    Flink provides excellent horizontal scalability, making it suitable for handling large data streams and high-throughput applications.
  • Fault tolerance
    Flink's checkpointing mechanism ensures fault-tolerance, maintaining data state consistency even after failures.
  • Ease of integration
    Flink integrates well with other big data tools and ecosystems, facilitating broader data architecture designs.
  • Real-time processing
    It excels at processing data in real-time, allowing for immediate insights and action on streaming data.
  • Community and support
    Being a part of the Apache Software Foundation, Flink benefits from a large community and comprehensive documentation.
  • Complex event processing
    It supports complex event processing, which is essential for many real-time applications.

Recommended for

  • real-time analytics
  • stream data processing
  • complex event processing
  • machine learning in streaming applications
  • applications requiring high-throughput and low-latency processing
  • companies looking for robust fault-tolerance in distributed systems

Analysis of Sumo Logic

Overall verdict

  • Overall, Sumo Logic is a strong solution for log management and analytics, particularly for organizations operating in cloud environments. Its comprehensive set of features and focus on security make it a reliable choice for businesses looking to gain deeper insights into their IT infrastructure.

Why this product is good

  • Sumo Logic is considered a good choice for many organizations due to its powerful cloud-native analytics capabilities. It provides real-time insights across various types of machine data and helps in monitoring, troubleshooting, and securing applications. Its scalability allows it to handle vast amounts of data efficiently, and it integrates seamlessly with a variety of cloud and on-premises solutions. Additionally, Sumo Logic offers advanced threat detection and operational intelligence, which are valuable for modern IT operations and security teams.

Recommended for

  • Organizations using cloud-native applications
  • Businesses needing real-time operational and security insights
  • Enterprises seeking scalable log management solutions
  • IT teams focused on proactive monitoring and troubleshooting
  • Security teams requiring advanced threat detection capabilities

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

Sumo Logic videos

Sumo Logic 2013 Year in Review

More videos:

  • Demo - Next Generation Log Management & Analytics - Demo of Sumo Logic

Category Popularity

0-100% (relative to Apache Flink and Sumo Logic)
Big Data
100 100%
0% 0
Monitoring Tools
0 0%
100% 100
Stream Processing
100 100%
0% 0
Log Management
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 Flink and Sumo Logic

Apache Flink Reviews

We have no reviews of Apache Flink yet.
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Sumo Logic Reviews

The 10 Best Nagios Alternatives in 2024 (Paid and Open-source)
Sumo Logic is yet another tempting Nagios alternative, especially appealing to large corporations, while also offering notable infrastructure monitoring capabilities. One standout feature of Sumo Logic is its utilization of cloud-based machine learning, which proves invaluable in efficiently managing vast amounts of data concurrently, making it particularly advantageous for...
Source: betterstack.com
10 Best Grafana Alternatives [2023 Comparison]
Sumo Logic is able to process big data, which means that it is aimed at companies that have a lot of data. In other words, Sumo Logic is aimed at big corporations with big budgets.
Source: sematext.com
11 Best Splunk Alternatives
Sumo Logic is a SaaS-based log management application that can monitor both on-premises and cloud-based services. The platform includes integrations for AWS, Microsoft Azure, Google Cloud, Kubernetes, and Docker, allowing it to work alongside your current tools and services.
8 Dynatrace Alternatives to Consider in 2021
Sumo Logic is an APM platform that promises faster troubleshooting with integrated logs, metrics, and traces. It focuses on cloud operations and providing analytics to support developers. It has multi-cloud support with over 150 apps that you can integrate with your work. It promises security, scalability, reliability, and performance by ensuring that data is unlimited for...
Source: scoutapm.com
Top 5 NGINX Log Analyzer Tools – Driving Business Growth with Data
Sumo Logic offers an application to analyze NGINX server logs. In addition to analyzing NGINX server performance, the tool can monitor complex transactions and track usage patterns. It uses machine learning capabilities to efficiently analyze huge amounts of logs. The unified logging system enables developers to monitor and troubleshoot issues in real-time, allowing faster...

Social recommendations and mentions

Based on our record, Apache Flink seems to be a lot more popular than Sumo Logic. While we know about 41 links to Apache Flink, we've tracked only 1 mention of Sumo Logic. 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 Flink mentions (41)

  • What is Apache Flink? Exploring Its Open Source Business Model, Funding, and Community
    Continuous Learning: Leverage online tutorials from the official Flink website and attend webinars for deeper insights. - Source: dev.to / 30 days ago
  • Is RisingWave the Next Apache Flink?
    Apache Flink, known initially as Stratosphere, is a distributed stream processing engine initiated by a group of researchers at TU Berlin. Since its initial release in May 2011, Flink has gained immense popularity in both academia and industry. And it is currently the most well-known streaming system globally (challenge me if you think I got it wrong!). - Source: dev.to / about 1 month ago
  • Every Database Will Support Iceberg — Here's Why
    Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration — Spark, Flink, Trino, DuckDB, Snowflake, RisingWave — can read and/or write Iceberg data directly. - Source: dev.to / about 2 months ago
  • RisingWave Turns Four: Our Journey Beyond Democratizing Stream Processing
    The last decade saw the rise of open-source frameworks like Apache Flink, Spark Streaming, and Apache Samza. These offered more flexibility but still demanded significant engineering muscle to run effectively at scale. Companies using them often needed specialized stream processing engineers just to manage internal state, tune performance, and handle the day-to-day operational challenges. The barrier to entry... - Source: dev.to / about 2 months ago
  • Twitter's 600-Tweet Daily Limit Crisis: Soaring GCP Costs and the Open Source Fix Elon Musk Ignored
    Apache Flink: Flink is a unified streaming and batching platform developed under the Apache Foundation. It provides support for Java API and a SQL interface. Flink boasts a large ecosystem and can seamlessly integrate with various services, including Kafka, Pulsar, HDFS, Iceberg, Hudi, and other systems. - Source: dev.to / 2 months ago
View more

Sumo Logic mentions (1)

  • Roadmap for July
    He's coming with years of experience of having architected systems at Uber, Flock, Sumo Logic and was a founding engineer who helped design the cryptography primitives at Zeta. Someone of his caliber coming onboard means that we'll be able to ship nicer things faster. 🎉. Source: almost 4 years ago

What are some alternatives?

When comparing Apache Flink and Sumo Logic, 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.

Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.

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

Dynatrace - Cloud-based quality testing, performance monitoring and analytics for mobile apps and websites. Get started with Keynote today!

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

LogicMonitor - LogicMonitor is the SaaS performance monitoring platform for the world's best IT teams. Deploy Fast, Monitor More, Improve Ops.