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Corral vs Splunk: What are the differences?
Developers describe Corral as "A serverless MapReduce framework written for AWS Lambda". Corral is a MapReduce framework designed to be deployed to serverless platforms, like AWS Lambda. It presents a lightweight alternative to Hadoop MapReduce. On the other hand, Splunk is detailed as "Search, monitor, analyze and visualize machine data". It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
Corral and Splunk belong to "Big Data Tools" category of the tech stack.
Corral is an open source tool with 632 GitHub stars and 22 GitHub forks. Here's a link to Corral's open source repository on GitHub.
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Learn MorePros of Corral
Pros of Splunk
Pros of Corral
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Pros of Splunk
- API for searching logs, running reports3
- Alert system based on custom query results3
- Splunk language supports string, date manip, math, etc2
- Dashboarding on any log contents2
- Custom log parsing as well as automatic parsing2
- Query engine supports joining, aggregation, stats, etc2
- Rich GUI for searching live logs2
- Ability to style search results into reports2
- Granular scheduling and time window support1
- Query any log as key-value pairs1
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Cons of Corral
Cons of Splunk
Cons of Corral
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Cons of Splunk
- Splunk query language rich so lots to learn1
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- No public GitHub repository available -
What is Corral?
Corral is a MapReduce framework designed to be deployed to serverless platforms, like AWS Lambda. It presents a lightweight alternative to Hadoop MapReduce.
What is Splunk?
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
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What companies use Corral?
What companies use Splunk?
What companies use Corral?
No companies found
What companies use Splunk?
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What tools integrate with Corral?
What tools integrate with Splunk?
What tools integrate with Corral?
What tools integrate with Splunk?
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What are some alternatives to Corral and Splunk?
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
PostgreSQL
PostgreSQL is an advanced object-relational database management system
that supports an extended subset of the SQL standard, including
transactions, foreign keys, subqueries, triggers, user-defined types
and functions.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
Amazon S3
Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web