Software Alternatives, Accelerators & Startups

Spark Streaming VS LogicMonitor

Compare Spark Streaming VS LogicMonitor and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Spark Streaming logo Spark Streaming

Spark Streaming makes it easy to build scalable and fault-tolerant streaming applications.

LogicMonitor logo LogicMonitor

LogicMonitor is the SaaS performance monitoring platform for the world's best IT teams. Deploy Fast, Monitor More, Improve Ops.
  • Spark Streaming Landing page
    Landing page //
    2022-01-10
  • LogicMonitor Landing page
    Landing page //
    2023-10-18

Spark Streaming features and specs

  • Scalability
    Spark Streaming is highly scalable and can handle large volumes of data by distributing the workload across a cluster of machines. It leverages Apache Spark's capabilities to scale out easily and efficiently.
  • Integration
    It integrates seamlessly with other components of the Spark ecosystem, such as Spark SQL, MLlib, and GraphX, allowing for comprehensive data processing pipelines.
  • Fault Tolerance
    Spark Streaming provides fault tolerance by using Spark's micro-batching approach, which allows the system to recover data in case of a failure.
  • Ease of Use
    Spark Streaming provides high-level APIs in Java, Scala, and Python, making it relatively easy to develop and deploy streaming applications quickly.
  • Unified Platform
    It provides a unified platform for both batch and streaming data processing, allowing reuse of code and resources across different types of workloads.

Possible disadvantages of Spark Streaming

  • Latency
    Spark Streaming operates on a micro-batch processing model, which introduces latency compared to real-time processing. This may not be suitable for applications requiring immediate responses.
  • Complexity
    While it integrates well with other Spark components, building complex streaming applications can still be challenging and may require expertise in distributed systems and stream processing concepts.
  • Resource Management
    Efficiently managing cluster resources and tuning the system can be difficult, especially when dealing with variable workload and ensuring optimal performance.
  • Backpressure Handling
    Handling backpressure effectively can be a challenge in Spark Streaming, requiring careful management to prevent resource saturation or data loss.
  • Limited Windowing Support
    Compared to some stream processing frameworks, Spark Streaming has more limited options for complex windowing operations, which can restrict some advanced use cases.

LogicMonitor features and specs

  • Comprehensive Monitoring
    LogicMonitor provides end-to-end IT infrastructure monitoring, including servers, networks, applications, and cloud services, ensuring holistic visibility.
  • Scalability
    Designed to handle both small and large enterprises, LogicMonitor can scale effortlessly with the growth of an organization’s IT infrastructure.
  • Ease of Deployment
    The platform is known for its quick setup process, allowing businesses to deploy and gain insights rapidly without significant downtime.
  • Customizable Dashboards
    Offers highly customizable dashboards that allow users to visualize data and metrics in a manner that suits their specific needs.
  • Automated Discovery
    Automatically discovers devices and applications within the network, significantly reducing the manual effort required for setup.
  • Third-party Integrations
    Supports numerous third-party integrations, enhancing its capabilities and making it easier to fit into an existing tech ecosystem.
  • Real-time Alerting
    Features real-time alerting mechanisms that help IT teams respond swiftly to potential issues, minimizing downtime and disruption.
  • Cloud and Hybrid Environment Support
    Offers robust support for cloud-based and hybrid environments, making it suitable for modern infrastructures that leverage diverse technologies.

Possible disadvantages of LogicMonitor

  • Cost
    Potentially high costs can be prohibitive for smaller organizations, particularly when additional features or large-scale deployments are involved.
  • Complexity
    Although powerful, the platform can be complex and may require a steep learning curve for users not familiar with advanced monitoring tools.
  • Resource Intensive
    The software can be resource-intensive, potentially necessitating additional hardware or computing resources to operate efficiently.
  • Customization Limitations
    Despite offering customization, certain areas may feel limited, especially for organizations with highly specific monitoring needs.
  • Dependency on Internet Connectivity
    Being a SaaS solution, LogicMonitor requires a reliable internet connection; any disruptions in connectivity can impact monitoring capabilities.
  • Alert Spam
    Without proper configuration, users might experience alert fatigue due to an overwhelming number of notifications.
  • Support Limitations
    While support is generally strong, some users report delays or less than satisfactory resolutions during peak times or with complex issues.

Analysis of LogicMonitor

Overall verdict

  • Yes, LogicMonitor is generally considered a good monitoring solution.

Why this product is good

  • LogicMonitor is praised for its comprehensive monitoring capabilities, ease of use, and scalability. It supports a wide range of technologies and offers robust reporting and alerting features. Users appreciate its cloud-based nature, which allows for quick deployment and minimal maintenance.

Recommended for

  • IT teams looking for a scalable, cloud-based monitoring solution.
  • Organizations seeking a tool with strong reporting and alerting capabilities.
  • Businesses that need to monitor a wide array of technologies and devices.

Spark Streaming videos

Spark Streaming Vs Kafka Streams || Which is The Best for Stream Processing?

More videos:

  • Tutorial - Spark Streaming Vs Structured Streaming Comparison | Big Data Hadoop Tutorial

LogicMonitor videos

An Introduction to LogicMonitor

More videos:

  • Review - Step Inside LogicMonitor [OUTDATED 2/4/20]
  • Review - Ted Baker Customer Fireside Chat | LogicMonitor Level Up Event June 2019

Category Popularity

0-100% (relative to Spark Streaming and LogicMonitor)
Stream Processing
100 100%
0% 0
Monitoring Tools
0 0%
100% 100
Data Management
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 Spark Streaming and LogicMonitor

Spark Streaming Reviews

We have no reviews of Spark Streaming yet.
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LogicMonitor Reviews

Top 10 PRTG Alternatives for Monitoring Networks and IT Infrastructure
If you’re not looking to be overwhelmed with network alerts, consider using LogicMonitor to automatically identify and take action for the most important alerts with 90% less noise.
7 Best Containerization Software Solutions of 2022
LogicMonitor’s dynamic topology mapping feature provides an at-a-glance view of your entire infrastructure, including networks, servers, containers, and more.
Source: techgumb.com
8 Dynatrace Alternatives to Consider in 2021
LogicMonitor is a massive proponent of hybrid IT. It is extensible and secure infrastructure monitoring on a single platform. With over 2,000 integrations available, it is a powerful package with many features that support configuration monitoring and AIOps early warning systems.
Source: scoutapm.com
Best New Relic Alternatives for Application Performance Monitoring (Cloud & SaaS)
Their Auto-Discover feature scans your systems and pulls data and information into easy to read graphs and data points that help you manage and monitor pain points. LogicMonitor helps you be more proactive about monitoring mission critical systems and lets you look at historical data to plan for future growth and capacity planning.
15 Best IT Monitoring Tools and Software
LogicMonitor offers monitoring templates and frequently expands to include new features that increase its functionality.
Source: blog.inedo.com

Social recommendations and mentions

Based on our record, Spark Streaming seems to be more popular. It has been mentiond 5 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.

Spark Streaming mentions (5)

  • 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
  • Streaming Data Alchemy: Apache Kafka Streams Meet Spring Boot
    Apache Spark Streaming: Offers micro-batch processing, suitable for high-throughput scenarios that can tolerate slightly higher latency. https://spark.apache.org/streaming/. - Source: dev.to / 10 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 / over 1 year ago
  • Machine Learning Pipelines with Spark: Introductory Guide (Part 1)
    Spark Streaming: The component for real-time data processing and analytics. - Source: dev.to / over 2 years ago
  • Spark for beginners - and you
    Is a big data framework and currently one of the most popular tools for big data analytics. It contains libraries for data analysis, machine learning, graph analysis and streaming live data. In general Spark is faster than Hadoop, as it does not write intermediate results to disk. It is not a data storage system. We can use Spark on top of HDFS or read data from other sources like Amazon S3. It is the designed... - Source: dev.to / over 3 years ago

LogicMonitor mentions (0)

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

What are some alternatives?

When comparing Spark Streaming and LogicMonitor, you can also consider the following products

Confluent - Confluent offers a real-time data platform built around Apache Kafka.

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

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data 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.

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

Zabbix - Track, record, alert and visualize performance and availability of IT resources