Mara vs Splunk
Overview
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CLI (Node.js)
Manual
Detailed Comparison
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data. | A lightweight ETL framework with a focus on transparency and complexity reduction. |
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 | Data integration pipelines as code: pipelines, tasks and commands are created using declarative Python code.; PostgreSQL as a data processing engine.; Extensive web ui. The web browser as the main tool for inspecting, running and debugging pipelines.; GNU make semantics. Nodes depend on the completion of upstream nodes. No data dependencies or data flows.; No in-app data processing: command line tools as the main tool for interacting with databases and data.; Single machine pipeline execution based on Python's multiprocessing. No need for distributed task queues. Easy debugging and and output logging.; Cost based priority queues: nodes with higher cost (based on recorded run times) are run first. |
Statistics | |
Stacks 772 | Stacks 5 |
Followers 1.0K | Followers 21 |
Votes 20 | Votes 3 |
Pros & Cons | |
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What are some alternatives to Splunk, Mara?
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.
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.
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
Distributed SQL Query Engine for Big Data
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 pulls together performance monitoring, logs, user experience and synthetic monitoring that tools organizations need to troubleshoot performance issues faster.
