Azure HDInsight vs Splunk

Overview

Splunk

Stacks773

Followers1.0K

Votes20

Azure HDInsight

Stacks29

Followers138

Votes0

Azure HDInsight vs Splunk: What are the differences?

Developers describe Azure HDInsight as "A cloud-based service from Microsoft for big data analytics". It is a cloud-based service from Microsoft for big data analytics that helps organizations process large amounts of streaming or historical data. 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.

Azure HDInsight can be classified as a tool in the "Big Data as a Service" category, while Splunk is grouped under "Big Data Tools".

Some of the features offered by Azure HDInsight are:

Fully managed
Full-spectrum
Open-source analytics service in the cloud for enterprises

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

According to the StackShare community, Splunk has a broader approval, being mentioned in 67 company stacks & 170 developers stacks; compared to Azure HDInsight, which is listed in 5 company stacks and 10 developer stacks.

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Detailed Comparison

Splunk	Azure HDInsight
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.	It is a cloud-based service from Microsoft for big data analytics that helps organizations process large amounts of streaming or historical 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	Fully managed; Full-spectrum; Open-source analytics service in the cloud for enterprises
Statistics
Stacks 773	Stacks 29
Followers 1.0K	Followers 138
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	IntelliJ IDEA Apache Spark Kafka Visual Studio Code Hadoop Apache Storm HBase Apache Hive Azure Data Factory Azure Active Directory

What are some alternatives to Splunk, Azure HDInsight?

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.

Google BigQuery

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

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.

Amazon Redshift

It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

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.