When comparing Sumo Logic vs jKool, the Slant community recommends Sumo Logic for most people. In the question“What are the best log aggregation & monitoring tools?” Sumo Logic is ranked 12th while jKool is ranked 34th. The most important reason people chose Sumo Logic is:
Sumo logic is entirely cloud based and very scalable.
Ranked in these QuestionsQuestion Ranking
Sumo logic is entirely cloud based and very scalable.
Pro Flexible licensing model
Licensing cost is primarily determined by daily ingest of logs, however this is averaged out over 30 days instead of locking a user out of their own data after an arbitrary number of license breaches.
Pro Truly multi-tenant
Sumo Logic is truly multi-tenant, a single instance running on the server can serve multiple groups of users.
Pro A large set of supporting Apps
Allows customers to quickly setup and start getting actionable insights from their infrastructure by using Apps that integrate with various different platforms out of the box.
Pro Subscriptions to real-time updates
Subscriptions to real-time updates from infrastructure systems gives users proactive detection of application anomalies, as well as performance, availability and capacity issues. This enables users to capture perishable insights into application issues that they would normally miss.
Pro Offers free option
JKool offers free option limited by daily data volume and retention. Easy to sign up and try. No commitment or credit card required to signup.
Pro Simple English-like query language
jKool uses JKQL (english like query language) to search real-time and historical events, metrics and transaction streams. It includes verbs like GET, SUBSCRIBE, COMPARE, etc. Compare allows comparison of events, activities and metrics.
Pro Open source connectors
jKool offers open source connectors available hosted on GitHub: syslog, log4j, slf4j, logback, jmx, Spark, HDFS, JMS, MQTT, Logstash etc.
Pro Analyze logs: syslog, log4j, logback and others
You can use the jKool log collectors to stream syslogs and other logs to a jKool and be able to view and analyze your logs in a graphical oriented way. jKool can show error rates, anomalies, exceptions, groups, time buckets, time windows, aggregations and apply math functions across all your logs.
Pro Supports Logstash as a datasource
jKool can consume incoming streams directly from Logstash. Combine Logstash with other streams to deliver a unified application view. Logstash integration is open source.
Pro True multi-tenancy
Supports concepts of data repositories, organizations, teams and users which allows logical data separation and access control.
Pro Real-time search
Search for events, transcations, metrics streams in real-time before data is indexed.
Pro Automatic anomaly detection
Helps to proactively detect potential anomalous behavior and prevent problems from occurring.
Pro Unique Visualization
Visualization is generated dynamically based on a data query as opposed to the typical canned views that have nothing to do with the specific query.
Pro More than log analyzer
jKool does much more than just log analysis. Examples: end-user monitoring, application performance, transaction tracking, business metrics and IoT. Developers can use APIs (java, REST) to build extensions for streaming, visualization. jKool provides a unified model for all time series machine data.
Pro Simple, easy to use, great UI
There are really only 2 things a user needs to do to show charts, graphs: 1) create a dashboard 2) Create viewlets. Each viewlets is bound with a JQKL query. JQKL queries can be typed in or built via a query builder for beginners. Pretty easy to get up and running without learning JQKL. There is also a UI tutorial once you logon to jKool.
Pro Self service dashboard for users with different responsibilities.
Provides situational awareness to users from their own perspective. The benefits are translated to reduction of support calls and visibility for each user, from their own angles into root causes of problems within a couple of clicks.
Pro Unified analytics support
Combines analytics for events, metrics (name, value pairs) and transactions with real-time and historical analytics in a single platform.
Pro Transaction Tracking & Discovery
jKool is able to automatically connect/stitch multiple events coming from multiple sources into a business transaction(s), measure performance, completion, progress. Transactions can be grouped into user defined sets (payment, claims, etc).
Pro Simple model: Stream Data->Run Queries->Analyze
Easy to use cloud based log and application analytics supporting standards such as Syslog, log4j, log files, end-user monitoring, transaction tracking. No schemas to define, agentless, no servers or storage to setup. Provides true transaction stitching and analytics -- track all transactions, 100% of the time. On-premise and cloud based (docker support available).
Con Useless need for collectors
You have to install a plugin on each host to collect logs, the collector is 89MBs and is written in Java. there's no reason to install a Java tool to send syslog data when Linux already does that natively. The memory footprint for Java-based apps is way too high and, in this case, completely unnecessary.
Con Difficult / Confusing Interface
The service and interface are very confusing.
Con There can be issues with smaller vendors
There may be some issues when using devices and services for smaller vendors which are not officially supported by Sumo Logic.
Con No free version
Con Indexing and search are very slow
Sending around 45000 events to it may take more than 3 minutes to show up in the interface.
Once they show up, a search may take up to 32 seconds to return results. On only 45000 events, the search should return in milliseconds.
Con Search is very difficult
Here's an example:
_sourceCategory=*windows* _sourceName=Security (4771 OR 4768 OR 4776 OR 4625) | parse regex "EventIdentifier = (?<event_id>\d+?);" | parse regex "ComputerName = \"(?<hostname>.+?)\"" | parse regex "(?:Result|Failure|Error) Code:.+?(?<result_code>0x[A-Fa-f\d]+)\b" nodrop | where result_code !="0x0" AND event_id in ("4771", "4768", "4776","4625") | count by hostname
Con Install is very painful
Con Does not support structured data
They don't support RFC5424 standard events
Con Doesn't seem to be very popular
JKool is a relatively new tool, as such, there don't seem to be many third party guides and tutorials other than from official sources from the JKool team.