jKool vs Data Dog

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.

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.

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.

jKool offers open source connectors available hosted on GitHub: syslog, log4j, slf4j, logback, jmx, Spark, HDFS, JMS, MQTT, Logstash etc.

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.

jKool can consume incoming streams directly from Logstash. Combine Logstash with other streams to deliver a unified application view. Logstash integration is open source.

Supports concepts of data repositories, organizations, teams and users which allows logical data separation and access control.

Search for events, transcations, metrics streams in real-time before data is indexed.

Helps to proactively detect potential anomalous behavior and prevent problems from occurring.

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.

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.

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.

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.

Combines analytics for events, metrics (name, value pairs) and transactions with real-time and historical analytics in a single platform.

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).

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).

5 VMs with 24h history and no alerts for free.

The Datadog Agent container runs with the other containers on a host. It collects metrics from neighboring containers and from the host. It can monitor 10 or 20 containers free per host license.