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  1. Stackups
  2. DevOps
  3. Log Management
  4. Log Management
  5. Delta Lake vs Splunk

Delta Lake vs Splunk

OverviewComparisonAlternatives

Overview

Splunk
Splunk
Stacks772
Followers1.0K
Votes20
Delta Lake
Delta Lake
Stacks105
Followers315
Votes0
GitHub Stars8.4K
Forks1.9K

Delta Lake vs Splunk: What are the differences?

# Delta Lake vs Splunk

Delta Lake and Splunk are two popular data management tools with distinct differences that cater to unique data handling needs.

1. **Primary Functionality**: Delta Lake is primarily a data lake storage layer that provides ACID transactions on top of big data. It ensures data consistency and reliability for big data workloads. Splunk, on the other hand, is a platform for searching, monitoring, and analyzing machine-generated big data, making it suitable for operational intelligence and security use cases.
2. **Data Sources**: Delta Lake is commonly used with Apache Spark for processing large amounts of data efficiently. It can handle structured, semi-structured, and unstructured data. Splunk, on the other hand, is designed to collect, index, and correlate real-time data from various sources like applications, servers, and devices to provide real-time insights.
3. **Querying Capabilities**: Delta Lake supports Spark SQL for querying and analyzing data stored in the lake. It allows users to run complex analytical queries on massive datasets. Splunk has its proprietary search processing language (SPL) that enables users to search, analyze, and visualize data stored in Splunk indexes with powerful query capabilities.
4. **Use Cases**: Delta Lake is commonly used in data engineering pipelines for data lakes and analytics use cases. It provides reliability and performance enhancements for big data workloads. Splunk, on the other hand, is more focused on IT operations, security, and compliance, helping organizations gain operational visibility, security monitoring, and real-time insights.
5. **Scaling Capabilities**: Delta Lake can scale horizontally to handle massive data volumes effectively. It can distribute data processing tasks across a cluster of machines for parallel processing. Splunk has built-in scalability features to handle high ingest rates and large data volumes, enabling real-time analytics and monitoring at scale.
6. **Community Support and Ecosystem**: Delta Lake is an open-source project with a growing community around it, contributing to its development and adoption. Splunk has a well-established ecosystem with a wide range of apps, add-ons, and community support for extending its functionalities and integrations with other systems.

In Summary, Delta Lake and Splunk differ in their primary functionality, supported data sources, querying capabilities, use cases, scaling capabilities, and community support and ecosystem.

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Detailed Comparison

Splunk
Splunk
Delta Lake
Delta Lake

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

An open-source storage layer that brings ACID transactions to Apache Spark™ and big data workloads.

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
ACID Transactions; Scalable Metadata Handling; Time Travel (data versioning); Open Format; Unified Batch and Streaming Source and Sink; Schema Enforcement; Schema Evolution; 100% Compatible with Apache Spark API
Statistics
GitHub Stars
-
GitHub Stars
8.4K
GitHub Forks
-
GitHub Forks
1.9K
Stacks
772
Stacks
105
Followers
1.0K
Followers
315
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
Apache Spark
Apache Spark
Hadoop
Hadoop
Amazon S3
Amazon S3

What are some alternatives to Splunk, Delta Lake?

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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