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  1. Stackups
  2. DevOps
  3. Log Management
  4. Log Management
  5. Logentries vs Splunk

Logentries vs Splunk

OverviewComparisonAlternatives

Overview

Logentries
Logentries
Stacks279
Followers174
Votes105
Splunk
Splunk
Stacks772
Followers1.0K
Votes20

Logentries vs Splunk: What are the differences?

Introduction

When comparing Logentries and Splunk in the realm of log management and analysis, there are key differences that distinguish the two platforms.

  1. Data Volume Handling: Logentries is suited for small to medium-sized businesses with lower data volumes, while Splunk excels in handling massive amounts of data from enterprise-level organizations, making it a more suitable option for large-scale operations.

  2. Ease of Use: Logentries offers a more user-friendly, intuitive interface that is easier to navigate for individuals who may be newer to log management, whereas Splunk can have a steeper learning curve due to its extensive feature set and customization options, targeting users with more technical expertise.

  3. Cost: Logentries offers a more affordable pricing structure suitable for small to medium-sized businesses with limited budgets, while Splunk is known for being more expensive, especially when used in environments with high data volumes, making it more feasible for larger enterprises with greater financial resources.

  4. Search Capabilities: Splunk is revered for its powerful search capabilities and the ability to perform complex queries across vast amounts of data efficiently, providing unparalleled flexibility in data analysis, whereas Logentries may have limitations in handling detailed, intricate searches at scale.

  5. Integration and Customization: Splunk provides extensive integration options with various third-party tools and systems, allowing for a high degree of customization and interoperability, whereas Logentries may have more limited integration capabilities and customization features, potentially limiting its functionality in certain environments.

  6. Scalability: Splunk is highly scalable, capable of growing with the needs of an organization as data volumes increase, making it a preferred choice for enterprises looking for a long-term log management solution that can adapt to expanding datasets, while Logentries may face limitations in scalability for organizations experiencing rapid growth in data volume.

In Summary, Logentries and Splunk differ significantly in their data volume handling, ease of use, cost, search capabilities, integration, customization, and scalability, making each platform more suitable for specific organizational requirements and preferences.

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Detailed Comparison

Logentries
Logentries
Splunk
Splunk

Logentries makes machine-generated log data easily accessible to IT operations, development, and business analysis teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users.

It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

Logs as Metrics - Extract field level values, analyze them using powerful search functions, and visualize them with detailed dashboards.;Dynamic Log Correlation - Dynamically group and correlate your logs in a single dashboard, or aggregate logs from a particular system to give an end-to-end view.;Live Tail - View your streaming logs in real-time and highlight important events to easily see errors or exceptions in your live data.;S3 Archiving - Backup your log data daily to long term and cost effective triple redundancy storage in a SOC 2 compliant data center.;Server Monitoring - Monitor critical server stats and auto-generate log data for real-time alerting, visualized trending and deep performance insight.;Open API - Build easy, out-of-the-box integrations using Logentries’ open API;leverage existing toolsets and system integrations, including HipChat, PagerDuty and Campfire.;Team-based Annotations - See team member comments, share expertise, and maintain context with the new team-based view of system activity and log events;identify and resolve issues together in real-time.
Predict and prevent problems with one unified monitoring experience; Streamline your entire security stack with Splunk as the nerve center; Detect, investigate and diagnose problems easily with end-to-end observability
Statistics
Stacks
279
Stacks
772
Followers
174
Followers
1.0K
Votes
105
Votes
20
Pros & Cons
Pros
  • 34
    Log search
  • 27
    Live logs
  • 19
    Easy setup
  • 14
    Heroku Add-on
  • 5
    Backup to S3
Pros
  • 3
    Alert system based on custom query results
  • 3
    API for searching logs, running reports
  • 2
    Splunk language supports string, date manip, math, etc
  • 2
    Custom log parsing as well as automatic parsing
  • 2
    Dashboarding on any log contents
Cons
  • 1
    Splunk query language rich so lots to learn
Integrations
cloudControl
cloudControl
Heroku
Heroku
AppFog
AppFog
AppHarbor
AppHarbor
Jelastic
Jelastic
Engine Yard Cloud
Engine Yard Cloud
Red Hat OpenShift
Red Hat OpenShift
PagerDuty
PagerDuty
Campfire
Campfire
HipChat
HipChat
No integrations available

What are some alternatives to Logentries, Splunk?

Papertrail

Papertrail

Papertrail helps detect, resolve, and avoid infrastructure problems using log messages. Papertrail's practicality comes from our own experience as sysadmins, developers, and entrepreneurs.

Logmatic

Logmatic

Get a clear overview of what is happening across your distributed environments, and spot the needle in the haystack in no time. Build dynamic analyses and identify improvements for your software, your user experience and your business.

Loggly

Loggly

It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.

Apache Spark

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Logstash

Logstash

Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.

Graylog

Graylog

Centralize and aggregate all your log files for 100% visibility. Use our powerful query language to search through terabytes of log data to discover and analyze important information.

Presto

Presto

Distributed SQL Query Engine for Big Data

Amazon Athena

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

Sematext

Sematext

Sematext pulls together performance monitoring, logs, user experience and synthetic monitoring that tools organizations need to troubleshoot performance issues faster.

Fluentd

Fluentd

Fluentd collects events from various data sources and writes them to files, RDBMS, NoSQL, IaaS, SaaS, Hadoop and so on. Fluentd helps you unify your logging infrastructure.

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