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Loggly VS Apache Spark

Compare Loggly VS Apache Spark and see what are their differences

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Loggly logo Loggly

The world's most popular cloud log management service delivers application intelligence. No Software. No Downloads. No Sweat. Free Trial!

Apache Spark logo Apache Spark

Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
  • Loggly Landing page
    Landing page //
    2023-01-05
  • Apache Spark Landing page
    Landing page //
    2021-12-31

Loggly videos

+ Add

Pingdom, Loggly, and Digital Experience Monitoring - SolarWinds Lab Episode #63

More videos:

  • Review - SolarWinds Lab Bits: Papertrail, Loggly in Observability Action

Apache Spark videos

+ Add

Weekly Apache Spark live Code Review -- look at StringIndexer multi-col (Scala) & Python testing

More videos:

  • Review - What's New in Apache Spark 3.0.0
  • Review - Apache Spark for Data Engineering and Analysis - Overview

Category Popularity

0-100% (relative to Loggly and Apache Spark)

Loggly

Apache Spark

Log Management
100 100%
Log Management
0% 0
Databases
0 0%
Databases
100% 100
Monitoring Tools
100 100%
Monitoring Tools
0% 0
Big Data
0 0%
Big Data
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 Loggly and Apache Spark

Loggly Reviews

10 Best Grafana Alternatives [2023 Comparison]
Another log management-focused Grafana alternative that we’re adding to this list is Loggly from SolarWinds. Loggly is a cloud-based service that allows users to transmit over HTTP/SYSLOg directly.
Source: sematext.com
11 Best Splunk Alternatives
Loggly is a free SaaS-based log monitoring application that can handle massive amounts of log data from any source. Loggly allows you to examine log events from various sources in real-time, including cloud platforms, databases, mobile apps, operating systems, and more. You can see a brief performance for systems across your environment on the dashboard, with metrics down to...
Source: www.ittsystems.com
Top 5 NGINX Log Analyzer Tools – Driving Business Growth with Data
SolarWinds® Loggly® is a powerful cloud-based tool designed to simplify and speed up log aggregation, monitoring, and analysis. It centralizes logs gathered from a distributed environment to correlate data for better analysis. Loggly makes log analysis simpler and faster and requires minimal configuration to set up. It can collect logs from various sources without installing...
Source: www.dnsstuff.com
Top 21 Log Management Software Tools
Loggly is a cloud-based log management services that can dig deep into extensive collections of log data in real-time while giving you the most crucial information, on how to improve your code and deliver a better customer experience. It offers custom tags that let you find related errors throughout your log data. Also, it has data analysis dashboard that gives you a visual...
Source: apiumacademy.com
Best DataDog Alternatives, Replacements & Competitors for Application & Log Monitoring
Loggly also allows you to integrate with the common DevOps tools, so that your team can share log analytics and real-time stream event logs. Its integration to apps such as HipChat, Slack, Jira, PagerDuty allows higher team collaboration. You can even integrate it with your tools with Loggly’s powerful API.
Source: www.pcwdld.com

Apache Spark Reviews

15 data science tools to consider using in 2021
Apache Spark is an open source data processing and analytics engine that can handle large amounts of data -- upward of several petabytes, according to proponents. Spark's ability to rapidly process data has fueled significant growth in the use of the platform since it was created in 2009, helping to make the Spark project one of the largest open source communities among big...
Source: searchbusinessanalytics.techtarget.com
Top 15 Kafka Alternatives Popular In 2021
Apache Spark is a well-known, general-purpose, open-source analytics engine for large-scale, core data processing. It is known for its high-performance quality for data processing – batch and streaming with the help of its DAG scheduler, query optimizer, and engine. Data streams are processed in real-time and hence it is quite fast and efficient. Its machine learning...
Source: www.spec-india.com
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Spark is an open-source and flexible in-memory framework which serves as an alternative to map-reduce for handling batch, real-time analytics and data processing workloads. It provides native bindings for the Java, Scala, Python, and R programming languages, and supports SQL, streaming data, machine learning and graph processing. From its beginning in the AMPLab at...
Source: www.analyticsinsight.net

Social recommendations and mentions

Based on our record, Apache Spark seems to be a lot more popular than Loggly. While we know about 56 links to Apache Spark, we've tracked only 1 mention of Loggly. 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.

Loggly mentions (1)

  • “Print” Is the Only Debug Tool You Need
    Print works on Staging and Production: It’s not easy to work with debug tools when you’re dealing with code running on the server. On the other hand, print statements work there too. Even if you don’t have access to STDOUT, you can write statements to a file or send them to a logging server/service (e.g, Loggly). - Source: dev.to / almost 2 years ago

Apache Spark mentions (56)

  • Groovy 🎷 Cheat Sheet - 01 Say "Hello" from Groovy
    Recently I had to revisit the "JVM languages universe" again. Yes, language(s), plural! Java isn't the only language that uses the JVM. I previously used Scala, which is a JVM language, to use Apache Spark for Data Engineering workloads, but this is for another post 😉. - Source: dev.to / 2 months ago
  • 🦿🛴Smarcity garbage reporting automation w/ ollama
    Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system. - Source: dev.to / 3 months ago
  • Go concurrency simplified. Part 4: Post office as a data pipeline
    Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 5 months ago
  • Five Apache projects you probably didn't know about
    Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 5 months ago
  • Spark – A micro framework for creating web applications in Kotlin and Java
    A JVM based framework named "Spark", when https://spark.apache.org exists? - Source: Hacker News / 11 months ago
View more

What are some alternatives?

When comparing Loggly and Apache Spark, you can also consider the following products

Splunk - Splunk's operational intelligence platform helps unearth intelligent insights from machine data.

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

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.

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

Sumo Logic - Sumo Logic is a secure, purpose-built cloud-based machine data analytics service that leverages big data for real-time IT insights

Hadoop - Open-source software for reliable, scalable, distributed computing

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