Qlik vs Splunk

Overview

Splunk

Stacks772

Followers1.0K

Votes20

Qlik

Stacks40

Followers33

Votes0

Qlik vs Splunk: What are the differences?

Data Source: Qlik focuses on analyzing and visualizing structured data while Splunk specializes in analyzing machine-generated data like logs, events, and metrics.
Deployment: Qlik is typically deployed on-premises or in a private cloud, whereas Splunk offers both on-premises and cloud-based deployment options.
Use Cases: Qlik is commonly used for business intelligence and data visualization, while Splunk is extensively used for IT operations, security, and compliance.
Architecture: Qlik utilizes an in-memory data engine for faster processing and analysis, whereas Splunk uses an index-based architecture for efficient searching and indexing of data.
Customization: Qlik offers a more user-friendly interface with drag-and-drop customization options for building dashboards, while Splunk requires more technical expertise for customizing searches and visualizations.
Pricing Model: Qlik generally follows a per-user or per-server pricing model, whereas Splunk pricing is typically based on data ingestion volume, making it more scalable for organizations with fluctuating data needs.

In Summary, Qlik and Splunk differ in their focus on data sources, deployment options, use cases, architecture, customization capabilities, and pricing models.

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Detailed Comparison

Splunk	Qlik
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.	Turn your data into business value faster with Qlik, the only end-to-end data integration and data analytics solutions for modern business intelligence.
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	Streaming data pipelines with change data capture; Automate the process from raw to analytics-ready data; Make data easily accessible with an enterprise data catalog
Statistics
Stacks 772	Stacks 40
Followers 1.0K	Followers 33
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, Qlik?

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.

Metabase

It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.

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.

Related Comparisons

Qlik vs Splunk: What are the differences?

Data Source: Qlik focuses on analyzing and visualizing structured data while Splunk specializes in analyzing machine-generated data like logs, events, and metrics.
Deployment: Qlik is typically deployed on-premises or in a private cloud, whereas Splunk offers both on-premises and cloud-based deployment options.
Use Cases: Qlik is commonly used for business intelligence and data visualization, while Splunk is extensively used for IT operations, security, and compliance.
Architecture: Qlik utilizes an in-memory data engine for faster processing and analysis, whereas Splunk uses an index-based architecture for efficient searching and indexing of data.
Customization: Qlik offers a more user-friendly interface with drag-and-drop customization options for building dashboards, while Splunk requires more technical expertise for customizing searches and visualizations.
Pricing Model: Qlik generally follows a per-user or per-server pricing model, whereas Splunk pricing is typically based on data ingestion volume, making it more scalable for organizations with fluctuating data needs.

In Summary, Qlik and Splunk differ in their focus on data sources, deployment options, use cases, architecture, customization capabilities, and pricing models.

Qlik vs Splunk

Overview