Best Log Analysis Software - Page 6

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Graylog

SIEM and log management in one platform Graylog helps security and IT teams detect, investigate, and respond to threats faster, using explainable AI and real-time data correlation to turn large volumes of log data into decisions they can act on. More than 60,000 organizations worldwide use Graylog for visibility and control over their IT environments. The problem Security analysts and IT professionals spend their days sifting through vast amounts of log data to find the anomalies that matter, track incidents, and prove compliance with regulatory standards. Most of that data is noise. -Too many alerts that do not matter, and the one that does is buried. -Forensic evidence scattered across tools, so investigations stall. -Audit documentation assembled by hand the week before the deadline. Catch the patterns rules miss Anomaly detection flags unusual patterns in your data so your team sees behavior that signature-based rules leave in the blind spot. Real-time correlation connects related events as they arrive. Investigations that build themselves Guided investigations walk analysts through complex incidents. Automated workflows handle the repetitive tasks, and AI-driven summaries surface the affected assets, the incident timeline, and the high-priority findings. Analysts focus on what matters instead of excessive data. Work the alerts that matter first Risk scores rank each alert by the severity of what fired and the importance of the assets involved, so a port scan against a database of client PII outranks the same scan against a user laptop. With centralized log management, every log stays a single log, giving your team the historic evidence to complete forensic investigations in one place. One platform, three products Graylog fits the team you have: -Graylog Open for log management on an open foundation. -Graylog Enterprise for IT operations and log management at scale. -Graylog Security for detection, investigation, and response.

Average Rating: 4.4/5.0

Total Reviews: 110

How Do G2 Users Rate Graylog?

  • Alerts: 8.6/10 (Category avg: 8.7/10)
  • Data Sources: 8.5/10 (Category avg: 8.9/10)
  • Has the product been a good partner in doing business?: 8.4/10 (Category avg: 8.9/10)
  • Metric and Event Data: 9.0/10 (Category avg: 8.7/10)

Who Is the Company Behind Graylog?

  • Seller: Graylog
  • Company Website:
  • Year Founded: 2009
  • HQ Location: Houston, US
  • Twitter: @graylog2
    9,115 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    124 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Software Engineer
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 44% Medium, 32% Small

What Do G2 Reviewers Say About Graylog?

AI-generated summary from verified user reviews

Pros
  • Users value the cost optimization of Graylog, finding it reliable and compliant with industry standards.
  • Users find the detailed API information essential for effective debugging, enhancing their daily workflow significantly.
  • Users find the detailed API information invaluable for effective debugging, preventing potential dead ends in troubleshooting.
  • Users find the detailed API information provided by Graylog extremely helpful for effective debugging processes.
  • Users praise Graylog for its reliable and cost-effective pricing, aligning well with industry standards and needs.
Cons
  • Users find Graylog's complexity frustrating, as it often leads to wasted time during debugging and review processes.
  • Users face debugging difficulties with Graylog, often leading to wasted time and frustration during troubleshooting.
  • Users experience difficulties with integration issues, limiting the compatibility of Graylog with other platforms.
  • Users find the learning curve to be challenging, leading to time wasted instead of efficient debugging and reviews.
  • Users experience time consumption with Graylog, finding that it complicates workflows and wastes valuable debugging time.

What Are Recent G2 Reviews of Graylog?

What Are G2 Users Discussing About Graylog?

Updated August 2026.

How Many Log Analysis Software Products Does G2 Track?

Total Products under this Category: 111

Category Stats (Oct 2026)

  • Average Rating: 4.46/5 The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: Cribl (+2.86%) - Among all products in this category, Cribl recorded the largest rating increase compared to last month

Last updated: October 21, 2026

How Does G2 Rank Log Analysis Software Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 10,100+ Authentic Reviews
  • 111+ Products
  • Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.

G2 Grid® for Log Analysis Software

G2 Grid® for Log Analysis Software plotting products by satisfaction and market presence

Highlighted products: Datadog, Cribl, Coralogix, New Relic, Sentry, Elastic Observability, Sumo Logic, and Dynatrace.

Underlying data: [Grid® JSON](https://www.g2.com/categories/log-analysis/grids.json?focus%5B%5D=datadog&focus%5B%5D=cribl-2026-07-02&focus%5B%5D=coralogix&focus%5B%5D=new-relic&focus%5B%5D=sentry&focus%5B%5D=elastic-observability&focus%5B%5D=sumo-logic&focus%5B%5D=dynatrace)

AuditSSH

AuditSSH is an application developed for Linux-based systems that aims to fill the trusted external access gap by acting as a secure and monitored gateway that maintainers can use to gain access to the requested systems without compromising their integrity.

Average Rating: 3.5/5.0

Total Reviews: 1

Who Is the Company Behind AuditSSH?

Who Uses This Product?

  • Company Size: 100% Medium

Azure Data Explorer

Every company has a mission. What's ours? To empower every person and every organization to achieve more. We believe technology can and should be a force for good and that meaningful innovation contributes to a brighter world in the future and today. Our culture doesn’t just encourage curiosity; it embraces it. Each day we make progress together by showing up as our authentic selves. We show up with a learn-it-all mentality. We show up cheering on others, knowing their success doesn't diminish our own. We show up every day open to learning our own biases, changing our behavior, and inviting in differences. When we show up, we achieve more together. Microsoft operates in 190 countries and is made up of more than 220,000 passionate employees worldwide.

Who Is the Company Behind Azure Data Explorer?

  • Seller: Microsoft
  • Year Founded: 1975
  • HQ Location: Redmond, Washington
  • Twitter: @microsoft
    13,091,739 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    232,750 employees on LinkedIn®
  • Ownership: MSFT

Blesk

Blesk is a log management software that performs all aspects of network monitoring from a single machine. Blesk layers are added bringing enhanced features and a uniform graphical interface.

Who Is the Company Behind Blesk?

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Cryptolog

CRYPTOSIM is a SIEM software with exceptional correlation and analysis features, serving as a detection and controlling platform that can be integrated with CRYPTOLOG log manager, to provide organizations with threat detection and security risk evaluation on network behavior and performance.

Who Is the Company Behind Cryptolog?

  • Seller: CRYPTTECH
  • Year Founded: 2006
  • HQ Location: Istanbul, TR
  • Twitter: @crypttech
    1,090 Twitter followers
  • LinkedIn® Page: tr.linkedin.com
    72 employees on LinkedIn®

Glassbeam

Glassbeam provides a platform that can ingest any complex log file and scale from gigabytes to terabytes of data per day. With its patented technology and a powerful proprietary language to build analytics from Log data in a single step, Glassbeam can increase your time to value by 100x

Who Is the Company Behind Glassbeam?

Gravwell

Gravwell is a log analysis and monitoring platform built on the principle that you need to be able to ask any question of your data and get answers quickly.  To achieve this goal the platform has been built around four pillars - Scalability, Ingestion of any data source, Easy search, and predictable pricing. Scalability: Gravwell is built by supercomputing experts which means scalability and efficiency are where we shine. We easily scale to over 100TB of data ingest per day and have delivered a comparable performance to our competitors with 40% fewer indexers and dramatically less ancillary infrastructure. Ingest any data source: To ask questions of your data you need to ingest it in its raw form; that is why Gravwell is structure on read and will take binary data like netflow, ipfix, and packets natively. Our hybrid indexing system ensures that no matter the data source, you can find needles in the haystack quickly and intuitively. Predictable pricing: If you are ingesting all of your data then you need to know what it is going to cost you. At Gravwell we only charge by the number of indexers in the cluster and don't penalize customers for unexpected data bursts or data sources with less value. Easy search: Learning the query language is quick and easy. At Gravwell we have a structured query language with query writing hints and error identification if something doesn't look quite right. Users who are familiar with Powershell, Linux command line, or SPL are up and running quickly and can become experts in days not months.

Who Is the Company Behind Gravwell?

  • Seller: Gravwell
  • Year Founded: 2017
  • HQ Location: Coeur dAlene, US
  • LinkedIn® Page: www.linkedin.com
    22 employees on LinkedIn®

HoneyLog

HoneyLog is a server-side web analytics platform that helps companies understand how AI crawlers, search engine bots, scrapers, automated agents, and human visitors interact with their websites. Unlike traditional analytics tools that rely primarily on JavaScript running in the browser, HoneyLog analyzes server and CDN logs. This gives teams visibility into traffic that conventional web analytics can't see, especially bot activity. HoneyLog identifies and analyzes crawlers such as Googlebot, Bingbot, GPTBot, ClaudeBot and other AI and search engine bots, helping SEO, GEO, marketing, publishing, e-commerce, and technical teams understand which automated agents are accessing their content, how often they visit, which pages they crawl, and how their behavior changes over time. The platform provides dashboards for bot and human traffic, AI crawler monitoring, crawl frequency and page-level analysis, robots.txt monitoring, sitemap insights, raw log exploration, alerts, and visibility into bot-driven infrastructure usage. HoneyLog can also help teams distinguish legitimate crawlers from suspicious or unidentified automated traffic. For SEO and Generative Engine Optimization (GEO) teams, HoneyLog provides a direct view of how search engines and AI platforms consume a website rather than relying only on rankings, referrals, or third-party estimates. Publishers and content owners can monitor which crawlers are accessing valuable content, while e-commerce companies can better understand how product pages, categories, and other important URLs are being discovered by bots. Infrastructure and engineering teams can use HoneyLog to investigate automated traffic, crawling patterns, bandwidth usage, and unnecessary server load. HoneyLog is built for a web where an increasing share of website traffic is generated by machines. It gives businesses a clearer picture of both human and bot activity so they can make better decisions about SEO, GEO, content accessibility, crawler management, and website infrastructure.

Who Is the Company Behind HoneyLog?

IBM Z Operational Log and Data Analytics

IBM Z Operational Log and Data Analytics is a solution focused on making mainframe data available in modern log analytics solutions to help accelerate incident identification within hybrid applications. There are a number of core capabilities that include a robust data pipeline supporting a wide breath of metrics and logs being generated by mainframes. In addition to the underlying data streaming component, IBM Z Operational Log and Data Analytics included various subsystem specific out-of-the-box dashboards and searches delivered to industry leading log analytics platform(s). Features: IBM Z specific log analytics platform (IBM Z Data Analytics Platform) Single collection point with IBM Z Common Data Provider Intuitive web configuration tool Ability to stream in near-realtime or batch mode Advanced data filtering IBM Z specific dashboards and insights Optimized data ingestion into Splunk Extensible with new data types Benefits: Increased hybrid cloud visibility Improve analytics flexibility Quicker time-to-value with root cause analysis Reduce cost and effort with reduction in analytics ingestion cost Simplified analytics experience Features: IBM Z specific log analytics platform (IBM Z Data Analytics Platform) Single collection point with IBM Z Common Data Provider Intuitive web configuration tool Ability to stream in near-realtime or batch mode Advanced data filtering IBM Z specific dashboards and insights Optimized data ingestion into Splunk Extensible with new data types Benefits: Increased hybrid cloud visibility Improve analytics flexibility Quicker time-to-value with root cause analysis Reduce cost and effort with reduction in analytics ingestion cost Simplified analytics experience Value proposition: Faster isolation of problems in hybrid applications -- Accelerates hybrid incident identification with near real-time operational analytics. Faster isolation of problems in hybrid applications -- Accelerates hybrid incident identification with near real-time operational analytics.

Who Is the Company Behind IBM Z Operational Log and Data Analytics?

  • Seller: IBM
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • Twitter: @IBMSecurity
    74,660 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®
  • Ownership: SWX:IBM

Log10

Log10 is a comprehensive platform designed to enhance the accuracy and reliability of AI applications, particularly those utilizing large language models (LLMs) in high-stakes, regulated industries. By integrating expert-level evaluation, real-time monitoring, and continuous improvement workflows, Log10 empowers development teams to deploy AI solutions with confidence and precision.

Who Is the Company Behind Log10?

  • Seller: Log10
  • Year Founded: 2023
  • HQ Location: San Francisco, US
  • LinkedIn® Page: www.linkedin.com
    12 employees on LinkedIn®

LogAnalysis

Who Is the Company Behind LogAnalysis?

  • Seller: XpoLog
  • Year Founded: 2005
  • HQ Location: New York, US
  • Twitter: @xpolog
    109 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    20 employees on LinkedIn®

LogEasy

QuarkWiz specializes in providing comprehensive cloud solutions, including cloud migration, managed services, and infrastructure optimization, tailored to meet the unique needs of businesses. As a trusted Google Cloud Partner, they focus on enhancing performance and security while reducing costs through innovative technologies like Generative AI and advanced cybersecurity measures. Their product offerings, such as LogEasy and ScaleFlow, aim to streamline operations and improve efficiency for clients across various industries. QuarkWiz is dedicated to empowering growth and transforming legacy systems into agile, cloud-native solutions for modern demands.

Who Is the Company Behind LogEasy?

  • Seller: QuarkWiz
  • Year Founded: 2018
  • HQ Location: Bengaluru East, IN
  • LinkedIn® Page: www.linkedin.com
    21 employees on LinkedIn®

Logflare

Predictable pricing for your project, Unlimited for your enterprise

Who Is the Company Behind Logflare?

Tian Lin
TL
Researched and written by Tian Lin
Updated October 3, 2024