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  5. OpenRefine vs Splunk

OpenRefine vs Splunk

OverviewDecisionsComparisonAlternatives

Overview

Splunk
Splunk
Stacks772
Followers1.0K
Votes20
OpenRefine
OpenRefine
Stacks33
Followers68
Votes0
GitHub Stars11.6K
Forks2.1K

OpenRefine vs Splunk: What are the differences?

What is OpenRefine? Desktop application for data cleanup and transformation. It is a powerful tool for working with messy data: cleaning it; transforming it from one format into another; and extending it with web services and external data.

What is Splunk? 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.

OpenRefine and Splunk belong to "Big Data Tools" category of the tech stack.

Some of the features offered by OpenRefine are:

  • Faceting
  • Clustering
  • Editing cells

On the other hand, Splunk provides the following key features:

  • 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

OpenRefine is an open source tool with 7.24K GitHub stars and 1.28K GitHub forks. Here's a link to OpenRefine's open source repository on GitHub.

According to the StackShare community, Splunk has a broader approval, being mentioned in 67 company stacks & 170 developers stacks; compared to OpenRefine, which is listed in 7 company stacks and 7 developer stacks.

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Advice on Splunk, OpenRefine

Sarah
Sarah

Jun 25, 2020

Needs adviceonOpenRefineOpenRefine

I'm looking for an open-source/free/cheap tool to clean messy data coming from various travel APIs. We use many different APIs and save the info in our DB. However, many duplicates cannot be easily recognized as such.

We would either write an algorithm or use smart technology/tools with ML to help with product management.

While there are many things to be considered, this is one feature that it should have:

"To avoid confusion, we need to merge the suppliers & products accordingly. Products and suppliers must be able to be merged and assigned separately.

Reason: It may happen that one supplier offers different products. E.g., 1 tour operator offers 3 products via 1 API, but only 1 product with 3 (or a different amount of) variations via a different API. Also, the commission may differ for products, which we need to consider. Very often, products that are live (are bookable in real-time) on via 1 API, but are not live on the other. E.g., Supplier product 1 & 2 of API1 are live, product 3 not. For the same supplier, API2 provides live availability for products 1, 2, and 3.

Summing up, when merging the suppliers (tour operators) we need to consider:

  • Are the products the same for all APIs?
  • Which booking system API gives a better commission? Note: Some APIs charge us 1-5% depending on the monthly sale, which needs to be considered
  • Which booking system provides live availability
  • Is it the same supplier, or is the name only similar?

Most of the time, the supplier names differ even if they are the same (e.g., API1 often names them XX Pty Ltd, while API2 leaves "Pty Ltd" out). Additionally, the product title, description, etc. differ.

We need to write logic and create an algorithm to find the duplicates & to merge, assign, or (de)activate the respective supplier or product. My previous developer started a module to merge the suppliers, which does not seem to work correctly. Also, it is way too time taking considering the high amount of products that we have.

I would recommend merging, assigning etc. products and suppliers only if our algorithm says it's 90- 100% the matching supplier/product. Otherwise, admins need to be able to check & modify this. E.g. everything with a lower possibility of matching will be matched automatically, but can be undone or modified.

The next time the cron job runs, this needs to be considered to avoid recreating duplicates & creating a mess."

I am not sure in what way OpenRefine can help to achieve this and what ML tool can be connected to learn from the decisions the product management team makes. Maybe you have an idea of how other travel portals deal with messy data, duplicates, etc.?

I'm looking for the cheapest solution for a start-up, but it should do the work properly.

19.2k views19.2k
Comments

Detailed Comparison

Splunk
Splunk
OpenRefine
OpenRefine

It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

It is a powerful tool for working with messy data: cleaning it; transforming it from one format into another; and extending it with web services and external data.

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
Faceting; Clustering; Editing cells; Reconciling; Extending web services
Statistics
GitHub Stars
-
GitHub Stars
11.6K
GitHub Forks
-
GitHub Forks
2.1K
Stacks
772
Stacks
33
Followers
1.0K
Followers
68
Votes
20
Votes
0
Pros & Cons
Pros
  • 3
    Alert system based on custom query results
  • 3
    API for searching logs, running reports
  • 2
    Ability to style search results into reports
  • 2
    Query engine supports joining, aggregation, stats, etc
  • 2
    Dashboarding on any log contents
Cons
  • 1
    Splunk query language rich so lots to learn
No community feedback yet
Integrations
No integrations available
Python
Python
Dask
Dask
Ludwig
Ludwig
Vertica
Vertica

What are some alternatives to Splunk, OpenRefine?

Papertrail

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

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

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

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

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

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

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

Presto

Distributed SQL Query Engine for Big Data

Amazon Athena

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

Sematext pulls together performance monitoring, logs, user experience and synthetic monitoring that tools organizations need to troubleshoot performance issues faster.

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