# Google Cloud Managed Service for Apache Spark Reviews **Vendor:** Google **Category:** [Big Data Processing And Distribution Systems](https://www.g2.com/categories/big-data-processing-and-distribution) **Average Rating:** 4.4/5.0 **Total Reviews:** 17 ## About Google Cloud Managed Service for Apache Spark Cloud Dataproc is a fast, easy-to-use, fully-managed cloud service for running Apache Spark and Apache Hadoop clusters in a simpler, more cost-efficient way. Operations that used to take hours or days take seconds or minutes instead, and you pay only for the resources you use (with per-second billing). Cloud Dataproc also easily integrates with other Google Cloud Platform (GCP) services, giving you a powerful and complete platform for data processing, analytics and machine learning. ## Google Cloud Managed Service for Apache Spark Reviews ### 1. Google Cloud Dataproc: One stop solution for all of your big-data-cluster needs **Rating:** 5.0/5.0 stars **Reviewed by:** Danveer S. | SDE II, Enterprise (> 1000 emp.) **Reviewed Date:** September 27, 2023 **What do you like best about Google Cloud Managed Service for Apache Spark?** 1. idle cluster deletion helps save costs when cluster is not in use. 2. autoscaling handles peak time load efficiently. 3. GCP support team is helpful in any critical issues. 4. Java API support is great. Cluster creation, Data-ETL and cluster deletion can be done in a single pipeline. **What do you dislike about Google Cloud Managed Service for Apache Spark?** 1. Cluster creation takes a few minutes of time which is not very convenient. 2.Sometimes autoscaling doesnot get triggered on time and pipelines fail with dataproc-agent-failure error **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** We are processing terrabites of data on dataproc and bringing consumer insights. It helps us in taking right decisions for our org. ### 2. A very powerful Hadoop Implementation without the fanfare of AWS EMR **Rating:** 4.5/5.0 stars **Reviewed by:** Edgar A. | Project Manager Architect / Google Cloud Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** June 02, 2023 **What do you like best about Google Cloud Managed Service for Apache Spark?** A great tool that maybe is not as popular as AWS EMR, but that punches above its weight. An elegant implementation. **What do you dislike about Google Cloud Managed Service for Apache Spark?** Using the GCP Storage and Processing paradigm can cause troubles in getting used to on-premise Hadoop users **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** A highly scalable solution that can help heavy users in their everyday jobs. ### 3. Managed/Scalable Data lake ETL in Google cloud **Rating:** 4.5/5.0 stars **Reviewed by:** Malathi M. | Programmer Analyst Executive, Enterprise (> 1000 emp.) **Reviewed Date:** July 05, 2022 **What do you like best about Google Cloud Managed Service for Apache Spark?** Google cloud DataProc best suits for below: Open Source, managed, scalable data analytics Serverless or manage clusters on your own Has good integrations with other GCP services Secure /cost-effective transient cluster with per-second billing Hadoop ecosystem in the managed GCP environment Easy to migrate the existing on-prem Hadoop workloads along with Hive warehouses. **What do you dislike about Google Cloud Managed Service for Apache Spark?** Dislikes are below: Scaling down has performance & other issues because of a cool-down period of the pending task. The serverless option should be improved with SLA-based scaling Still for streaming options go for Dataflow it still utilizes compute engine, not GKE (Google Kubernetes engine) Storing persistent GCS (HCFS - Hadoop compatible file system) data from Dataproc has some slowness due to the separation of compute/storage - it is our option to choose which storage for which processing It has HDFS storage allocated with each Dataproc node cluster, but not good for huge data storage locally **Recommendations to others considering Google Cloud Managed Service for Apache Spark:** Always check your use-case best suits with dataproc vs dataflow Also compare on Databricks delta lake pipelines best to use when you want to integrate with multiple GCP services like Pubsub, bigquey and many GCP services **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** Unified processing of both batch & stream ETL pipelines Simplifying the data lake building capabilities Scalable, managed custom compute engine golden image can be built with installed Hadoop ecosystem for faster startups. startup bootstrap scripts can be attached Also able to use for data science use cases. migration of existing on-prem Cloudera/HDP ambari clusters to data proc clusters in GCP Easy to build workflow scheduling Multi-modes of hive metastore creation ### 4. Best for Hadoop and Scala Spark **Rating:** 5.0/5.0 stars **Reviewed by:** Rahul K. | Big Data Engineer - I , Mid-Market (51-1000 emp.) **Reviewed Date:** September 26, 2019 **What do you like best about Google Cloud Managed Service for Apache Spark?** Dev-Ops expertise friendly, It is very easy to use. It gives almost 99.9% uptime and connection speed. A lot of documentation available on its website. A normal website user always look for cheap solutions. Google offers a 300 dollars free cloud service for 1 year which is very attractive for small website users. These are very scalable. **What do you dislike about Google Cloud Managed Service for Apache Spark?** Late entry to the Cloud marketing. Fewer features and services. Some feature are still in the Beta version. Fewer worldwide data centers. **Recommendations to others considering Google Cloud Managed Service for Apache Spark:** Dataproc clusters are very easy to use and maintain, with low cost. Google provided Gcloud SDK to easily access and use dataproc. **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** We have (our company client) preprod and production cluster fully maintained by Google dataproc. It helps us a lot maintaining them. We both can easily access the cluster. ### 5. Easy to use, dependable and powerful data processing tool **Rating:** 4.5/5.0 stars **Reviewed by:** Zachary B. | Junior Data Analyst, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** July 09, 2019 **What do you like best about Google Cloud Managed Service for Apache Spark?** That it's serverless - no infrastructure to manage. Big win. Bonus points for having Spark (plus API's), Hive and Hadoop preinstalled on the clusters. Optionality for launching managed instance clusters is quite nice to have as well **What do you dislike about Google Cloud Managed Service for Apache Spark?** It's a tough call - either the lack of enterprise admin and monitoring capabilities, or the inability to flexibly burst beyond fixed-capacity flat-rate pricing **Recommendations to others considering Google Cloud Managed Service for Apache Spark:** Dataproc is a great tool for big data processing. We chose it because of it's native support for Spark and Hive. Additionally, the ability to scale your data processing needs is very simple **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** We used Dataproc for big data processing, mainly because it has Spark installed on the clusters by default. The ability to launch and scale clusters quickly and easily is very nice ### 6. I love this product! **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Higher Education | Small-Business (50 or fewer emp.) **Reviewed Date:** April 10, 2019 **What do you like best about Google Cloud Managed Service for Apache Spark?** I like the ease of use for building clusters quickly and efficiently. At the same time I can resize them at any moment in time. I have plenty of nodes so that I don't have to be concerned about pipelines outgrowing my clusters. I like how the price is based on actual use, and that they gave me a $300 credit towards my project. **What do you dislike about Google Cloud Managed Service for Apache Spark?** Sometimes it can be not user friendly and clusters can take time to re start. Otherwise I have no other complaints. **Recommendations to others considering Google Cloud Managed Service for Apache Spark:** Try it out. You won't have much to complain about. **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** This use of clusters has allowed for predictability for opportunities in determining future sales, increased efficiency.  ### 7. Google Cloud **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Accounting | Mid-Market (51-1000 emp.) **Reviewed Date:** April 09, 2019 **What do you like best about Google Cloud Managed Service for Apache Spark?** The best way to manage Spark and Hadoop service that has been offered on the Google Cloud Platform. **What do you dislike about Google Cloud Managed Service for Apache Spark?** it doesn’t work with custom sources. For the standard computer, it is still the most expensive component **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** create managed clusters ### 8. Google Cloud dataproc **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Consumer Electronics | Mid-Market (51-1000 emp.) **Reviewed Date:** February 22, 2019 **What do you like best about Google Cloud Managed Service for Apache Spark?** This software is very good .it's ability to predict opportunities in sales or manufacturing from business records or data.Smooth IDE and seamless integration with multiple programming language options. **What do you dislike about Google Cloud Managed Service for Apache Spark?** not user friendly, would be more beneficial for data scientists or someone who specializes in IT.Clusters take time to re-start when billing is re-enabled. **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** Load balance is smooth between various clusters as jobs get distributed between the nodes.The predictability for opportunities in determining future sales, increased efficiency. Working towards running map reduce jobs for a recent project. ### 9. Use of Dataproc in Retail analytics **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Retail | Mid-Market (51-1000 emp.) **Reviewed Date:** April 11, 2019 **What do you like best about Google Cloud Managed Service for Apache Spark?** Use of Dataproc make the use of Hadoop Big Data solution in Cloud in Cloud seamless. It brings in the capability of storing non-structured data and decoupling with Compute so that it is scalable. . **What do you dislike about Google Cloud Managed Service for Apache Spark?** Key downsize has been unbale to create SQL frontend similar to Hive Metastore in Hadoop platform. BigQuery currently does not support AVRO and Parquet format. **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** Data Analytics in Cloud using Google ML capabilities. ### 10. Google Cloud DataProc **Rating:** 3.0/5.0 stars **Reviewed by:** Verified User in Alternative Medicine | Small-Business (50 or fewer emp.) **Reviewed Date:** March 22, 2019 **What do you like best about Google Cloud Managed Service for Apache Spark?** Cloud Dataproc is a fast, easy-to-use, fully-managed cloud service for running Apache Spark and Apache Hadoop clusters in a simpler, more cost-efficient way. Processing speeds are quick and efficient vs past technology. Cloud Dataproc also easily integrates with other Google Cloud Platforms **What do you dislike about Google Cloud Managed Service for Apache Spark?** So far the company has not run into any issues using the software. **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** This has helped with efficiency of sales and predictability for future endeavors ### 11. Dataproc experience **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Marketing and Advertising | Mid-Market (51-1000 emp.) **Reviewed Date:** April 11, 2019 **What do you like best about Google Cloud Managed Service for Apache Spark?** Its easy to spin up and close dataproc clusters on demand, easy access to bigquery and google cloud storage and run spark job. **What do you dislike about Google Cloud Managed Service for Apache Spark?** The spark job UI is not easily accessible. **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** deploy machine learning model in production ### 12. support for other operating system **Rating:** 3.0/5.0 stars **Reviewed by:** Verified User in Telecommunications | Enterprise (> 1000 emp.) **Reviewed Date:** April 10, 2019 **What do you like best about Google Cloud Managed Service for Apache Spark?** additional features over hadoop are required, more than kerberos and additional security and platform os support **What do you dislike about Google Cloud Managed Service for Apache Spark?** need to support redhat or other linux os **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** working on building analytics platfor for telcom utilizing additional products ### 13. Big Data Consultant **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** April 08, 2019 **What do you like best about Google Cloud Managed Service for Apache Spark?** User friendly. Good GUI. Does what it needs to d8. **What do you dislike about Google Cloud Managed Service for Apache Spark?** Too many steps when using ssh. Make it less steps to use when using the cloudshell. **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** Haven't used in that setting yet. Just practice. ### 14. Great to use! **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** March 13, 2019 **What do you like best about Google Cloud Managed Service for Apache Spark?** The graphical user interface for Dataproc makes it easier to create clusters and use it. **What do you dislike about Google Cloud Managed Service for Apache Spark?** It can be faster when it comes to computation time **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** I used it for creating Hadoop clusters and it was easy to use, interactive and maintainable ### 15. Good place to run hadoop clusters **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** October 17, 2018 **What do you like best about Google Cloud Managed Service for Apache Spark?** Smooth IDE and seamless integration with multiple programming language options. **What do you dislike about Google Cloud Managed Service for Apache Spark?** Clusters take time to re-start when billing is re-enabled. **Recommendations to others considering Google Cloud Managed Service for Apache Spark:** I would suggest everyone to give it a try when starting with cloud deployments and/or map reduce. **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** Working towards running map reduce jobs for a recent project. Load balance is smooth between various clusters as jobs get distributed between the nodes. ### 16. One of the best data prep tools on the cloud **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** September 25, 2018 **What do you like best about Google Cloud Managed Service for Apache Spark?** They support open source tools. Pricing is competitive. Really good performance. **What do you dislike about Google Cloud Managed Service for Apache Spark?** Nothing in particular to be disliked. They have combined all services and one place and sometimes difficult to navigate. **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** We apply as technology partner. Users could use our tool for data visualization after going through dataproc . ### 17. Google could Data proc review **Rating:** 3.5/5.0 stars **Reviewed by:** Leah D. | Renal Dietitian, Enterprise (> 1000 emp.) **Reviewed Date:** April 23, 2018 **What do you like best about Google Cloud Managed Service for Apache Spark?** this software was very helpful due to it's ability to predict opportunities in sales or manufacturing from business records or data **What do you dislike about Google Cloud Managed Service for Apache Spark?** not user friendly, would be more beneficial for data scientists or someone who specializes in IT **Recommendations to others considering Google Cloud Managed Service for Apache Spark:** assistance from someone who specializes in IT would be beneficial when initially using this software **What problems is Google Cloud Managed Service for Apache Spark solving and how is that benefiting you?** The predictability for opportunities in determining future sales, increased efficiency - [View Google Cloud Managed Service for Apache Spark pricing details and edition comparison](https://www.g2.com/products/google-cloud-managed-service-for-apache-spark/reviews?section=pricing&secure%5Bexpires_at%5D=2026-05-26+20%3A44%3A27+-0500&secure%5Bsession_id%5D=b92167e1-4f20-4fbb-8210-84d0a2099870&secure%5Btoken%5D=a232fc4a99827625ad570c4dae56d2cc98b47684a6727ba84831bba8864c90ad&format=llm_user) ## Google Cloud Managed Service for Apache Spark Features **Management** - Reporting - Auditing **Database** - Real-Time Data Collection - Data Distribution - Data Lake **Functionality** - Extraction - Transformation - Loading - Automation - Scalability **Integrations** - Hadoop Integration - Spark Integration **Platform** - Machine Scaling - Data Preparation - Spark Integration **Processing** - Cloud Processing - Workload Processing **Building Reports** - Data Transformation - Data Modeling - WYSIWYG Report Design - Integration APIs **Platform** - Mobile User Support - Customization - User, Role, and Access Management - Internationalization - Sandbox / Test Environments - Performance and Reliability - Breadth of Partner Applications ## Top Google Cloud Managed Service for Apache Spark Alternatives - [Databricks](https://www.g2.com/products/databricks/reviews) - 4.6/5.0 (754 reviews) - [Cloudera Data Platform](https://www.g2.com/products/cloudera-cloudera-data-platform/reviews) - 4.1/5.0 (131 reviews) - [Azure Data Factory](https://www.g2.com/products/azure-data-factory/reviews) - 4.6/5.0 (95 reviews)