Need advice about which tool to choose?Ask the StackShare community!
Add tool
Google Cloud Data Fusion vs Splunk: What are the differences?
# Introduction
In this analysis, we will highlight the key differences between Google Cloud Data Fusion and Splunk.
1. **Deployment and Scalability**: Google Cloud Data Fusion is a managed service that is fully integrated with other Google Cloud services, allowing for easy deployment and scalability. Splunk, on the other hand, is more focused on log management and analysis, requiring additional configuration and setup for deployment and scalability.
2. **Data Transformation and Integration**: Google Cloud Data Fusion provides a visual interface for creating data pipelines and integrating multiple data sources seamlessly. Splunk, while capable of handling large amounts of data, requires more manual configuration for data transformation and integration.
3. **Cost Structure**: Google Cloud Data Fusion follows a pay-as-you-go pricing model based on usage, providing cost efficiency for small to medium-sized businesses. Splunk, however, has a more complex pricing structure that can be costly for organizations with extensive data processing needs.
4. **Machine Learning and AI Capabilities**: Google Cloud Data Fusion offers built-in support for machine learning and AI tasks, enabling users to leverage advanced analytics capabilities. Splunk provides machine learning features through add-ons, requiring additional setup and integration for AI capabilities.
5. **Monitoring and Alerting**: Google Cloud Data Fusion includes monitoring and alerting features as part of the platform, simplifying the process of tracking data pipelines and detecting issues. Splunk offers robust monitoring and alerting capabilities but may require additional configuration for integration with existing systems.
6. **Community Support and Ecosystem**: Google Cloud Data Fusion benefits from Google's extensive cloud ecosystem and community support, providing users with resources for troubleshooting and development. Splunk also has a strong user community but may have a narrower focus on log management and analysis tools.
# In Summary, Google Cloud Data Fusion offers a more integrated and scalable solution for data transformation and analysis, while Splunk is more focused on log management with advanced monitoring and alerting capabilities.
Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn MorePros of Google Cloud Data Fusion
Pros of Splunk
Pros of Google Cloud Data Fusion
- Lower total cost of pipeline ownership1
Pros of Splunk
- API for searching logs, running reports3
- Alert system based on custom query results3
- Dashboarding on any log contents2
- Custom log parsing as well as automatic parsing2
- Ability to style search results into reports2
- Query engine supports joining, aggregation, stats, etc2
- Splunk language supports string, date manip, math, etc2
- Rich GUI for searching live logs2
- Query any log as key-value pairs1
- Granular scheduling and time window support1
Sign up to add or upvote prosMake informed product decisions
Cons of Google Cloud Data Fusion
Cons of Splunk
Cons of Google Cloud Data Fusion
Be the first to leave a con
Cons of Splunk
- Splunk query language rich so lots to learn1
Sign up to add or upvote consMake informed product decisions
What is Google Cloud Data Fusion?
A fully managed, cloud-native data integration service that helps users efficiently build and manage ETL/ELT data pipelines. With a graphical interface and a broad open-source library of preconfigured connectors and transformations, and more.
What is Splunk?
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
Need advice about which tool to choose?Ask the StackShare community!
Jobs that mention Google Cloud Data Fusion and Splunk as a desired skillset
What companies use Google Cloud Data Fusion?
What companies use Splunk?
What companies use Google Cloud Data Fusion?
No companies found
What companies use Splunk?
See which teams inside your own company are using Google Cloud Data Fusion or Splunk.
Sign up for StackShare EnterpriseLearn MoreSign up to get full access to all the companiesMake informed product decisions
What tools integrate with Google Cloud Data Fusion?
What tools integrate with Splunk?
What tools integrate with Google Cloud Data Fusion?
What tools integrate with Splunk?
Sign up to get full access to all the tool integrationsMake informed product decisions
Blog Posts
What are some alternatives to Google Cloud Data Fusion and Splunk?
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.
Apache Flink
Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
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.
Apache Hive
Hive facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage.
AWS Glue
A fully managed extract, transform, and load (ETL) service that makes it easy for customers to prepare and load their data for analytics.