Splunk vs Stackify

Overview

Stackify

Stacks113

Followers69

Votes56

Splunk

Stacks773

Followers1.0K

Votes20

Splunk vs Stackify: What are the differences?

Splunk: Search, monitor, analyze and visualize machine data. Splunk Inc. provides the leading platform for Operational Intelligence. Customers use Splunk to search, monitor, analyze and visualize machine data; Stackify: Performance. Metrics. Errors. Logs. One platform. Stackify offers the only developers-friendly innovative cloud based solution that fully integrates application performance management (APM) with error and log. Allowing them to easily monitor, detect and resolve application issues faster.

Splunk belongs to "Log Management" category of the tech stack, while Stackify can be primarily classified under "Performance Monitoring".

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CLI (Node.js)

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Detailed Comparison

Stackify	Splunk
Stackify offers the only developers-friendly innovative cloud based solution that fully integrates application performance management (APM) with error and log. Allowing them to easily monitor, detect and resolve application issues faster	It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
Application Performance Management (APM), Custom metrics, Log management. Application monitoring;Server Monitoring;DB & queries monitoring;Queues monitoring;Auto-discovery of new apps;Alerts;App Status Alerts;Email & SMS notification;Escalation rules;Errors aggregation, errors reporting;Alerts, trends;App reporting;Log Files aggregation & appending.Tail and search app & IIS logs;Windows event viewer;Remote secure Access;Access server logs, files, configurations;Role based access;Audit & reporting;App Metrics;Monitor performance counters;Custom Metrics via API;Monitor JVM mBeans;Application Performance;Track web page performance;Utilizing custom metrics to track performance of anything;	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 113	Stacks 773
Followers 69	Followers 1.0K
Votes 56	Votes 20
Pros & Cons
Pros 8 Error tracking 7 Log management 7 Easy setup 7 Monitoring 6 Real-time application health	Pros 3 API for searching logs, running reports 3 Alert system based on custom query results 2 Ability to style search results into reports 2 Query engine supports joining, aggregation, stats, etc 2 Custom log parsing as well as automatic parsing Cons 1 Splunk query language rich so lots to learn
Integrations
Amazon EC2 Slack Jira Rackspace Cloud Servers Microsoft Azure Azure DevOps	No integrations available

What are some alternatives to Stackify, Splunk?

New Relic

The world’s best software and DevOps teams rely on New Relic to move faster, make better decisions and create best-in-class digital experiences. If you run software, you need to run New Relic. More than 50% of the Fortune 100 do too.

Datadog

Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog!

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

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.

Raygun

Raygun gives you a window into how users are really experiencing your software applications. Detect, diagnose and resolve issues that are affecting end users with greater speed and accuracy.

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

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.

Logentries

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.

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.

AppSignal

AppSignal gives you and your team alerts and detailed metrics about your Ruby, Node.js or Elixir application. Sensible pricing, no aggressive sales & support by developers.