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  1. Stackups
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  5. Splunk vs Talend

Splunk vs Talend

OverviewDecisionsComparisonAlternatives

Overview

Splunk
Splunk
Stacks772
Followers1.0K
Votes20
Talend
Talend
Stacks297
Followers249
Votes0

Splunk vs Talend: What are the differences?

## Key Differences between Splunk and Talend

<Introduction>

1. **Data Integration vs. Data Analysis**: Splunk is primarily a data analysis platform that allows users to search, monitor, and analyze data while Talend is focused on data integration, helping users to integrate, transform, and manage data across different systems.
   
2. **Open Source vs. Proprietary Software**: Talend is an open-source platform, providing users with the ability to modify and customize the software to suit their needs, whereas Splunk is a proprietary software with limited customization options.
   
3. **Real-time vs. Batch Processing**: Splunk excels in real-time processing, allowing users to monitor and analyze data as it happens, while Talend is more suited for batch processing, where data is processed in predefined sets at scheduled intervals.
   
4. **Cost Structure**: Splunk is known for its high cost, as it charges based on the amount of data ingested, whereas Talend typically follows a subscription-based model, making it more cost-effective for organizations.
   
5. **User Interface**: Splunk provides a user-friendly interface that simplifies data analysis and visualization, making it ideal for non-technical users, while Talend's interface is more complex and caters to users with a technical background.
   
6. **Use Cases**: Splunk is commonly used for security information and event management (SIEM), log management, and operational intelligence, while Talend is preferred for data warehousing, data migration, and data governance tasks.

In Summary, Splunk is more focused on data analysis and real-time processing, while Talend specializes in data integration and offers an open-source option with a subscription-based cost structure.

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Advice on Splunk, Talend

karunakaran
karunakaran

Consultant

Jun 26, 2020

Needs advice

I am trying to build a data lake by pulling data from multiple data sources ( custom-built tools, excel files, CSV files, etc) and use the data lake to generate dashboards.

My question is which is the best tool to do the following:

  1. Create pipelines to ingest the data from multiple sources into the data lake
  2. Help me in aggregating and filtering data available in the data lake.
  3. Create new reports by combining different data elements from the data lake.

I need to use only open-source tools for this activity.

I appreciate your valuable inputs and suggestions. Thanks in Advance.

80.4k views80.4k
Comments

Detailed Comparison

Splunk
Splunk
Talend
Talend

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

It is an open source software integration platform helps you in effortlessly turning data into business insights. It uses native code generation that lets you run your data pipelines seamlessly across all cloud providers and get optimized performance on all platforms.

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
-
Statistics
Stacks
772
Stacks
297
Followers
1.0K
Followers
249
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

What are some alternatives to Splunk, Talend?

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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