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Google Cloud Dataproc description
Google Cloud Dataproc is a cloud-based service that makes it easier and cheaper for your company to analyze large amounts of data. It uses popular open-source tools like Apache Spark and Hadoop, but Google Cloud handles all the setup and management. This means your team can focus on getting insights from your data without worrying about the technical details. Dataproc is also integrated with other Google Cloud services for a complete data processing platform.
Who is Google Cloud Dataproc best for
We find that Google Cloud Dataproc is ideal for companies needing to analyze vast datasets using open-source tools like Apache Spark and Hadoop in the cloud. It's a managed service, so you can focus on insights, not infrastructure. We've noticed it particularly suits medium to large businesses across any sector.
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Perfect for mid-sized (101-1000 employees) to large enterprises (1000+).
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Great for companies across all industries seeking efficient big data processing solutions.
Google Cloud Dataproc features
Supported Open-source tool support: Run Hadoop, Spark, Flink, Presto and other open-source tools. |
Supported Managed and scalable service: Managed and scalable service for data processing. |
Supported Google Cloud integration: Integration with Google Cloud services (Vertex AI, BigQuery, Dataplex). |
Supported Cost-effective data lake modernization: Cost-effective data lake modernization and ETL. |
Supported Advanced security features: Advanced security features such as Kerberos, Apache Ranger. |
Supported Flexible cluster management: Flexible cluster management on Google Compute and Kubernetes. |
Supported Serverless Spark: Serverless Spark jobs. |
Google Cloud Dataproc pricing
The commentary is based on 2 reviews from Google Cloud Dataproc G2 reviews.
We find that Dataproc's pricing is generally perceived as competitive, with features like idle cluster deletion contributing to cost savings. However, be aware that some users have noted occasional issues with autoscaling potentially leading to unexpected costs.
See the Google Cloud Dataproc pricing page.
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Google Cloud Dataproc has a free trial.
Charges are calculated based on a rate of $0.01 per vCPU per hour.
Pricing mirrors that of Dataproc on Compute Engine, charged at $0.01 per vCPU per hour for virtual machines in Dataproc-created node pools.
Google Cloud Dataproc alternatives
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Google Cloud Dataproc FAQ
We find that Google Cloud Dataproc is a fully managed and scalable service for running open-source data processing tools like Spark and Hadoop. It simplifies big data analytics by handling the infrastructure, so your team can focus on extracting insights. It also integrates with other Google Cloud services.
What is Google Cloud Dataproc and what does Google Cloud Dataproc do?
We find that Google Cloud Dataproc is a fully managed and scalable service for running open-source data processing tools like Spark and Hadoop. It simplifies big data analytics by handling the infrastructure, so your team can focus on extracting insights. It also integrates with other Google Cloud services.
We find that Google Cloud Dataproc seamlessly integrates with various other Google Cloud services. This includes tools like Vertex AI for machine learning, BigQuery for data warehousing, and Dataplex for data lake management. This makes for a unified and efficient data platform.
How does Google Cloud Dataproc integrate with other tools?
We find that Google Cloud Dataproc seamlessly integrates with various other Google Cloud services. This includes tools like Vertex AI for machine learning, BigQuery for data warehousing, and Dataplex for data lake management. This makes for a unified and efficient data platform.
We find that Amazon EMR and Cloudera Data Platform are the main competitors for Google Cloud Dataproc. They offer similar capabilities for big data processing using open-source tools. Azure Data Lake Store focuses on storage, so it's less directly comparable.
What the main competitors of Google Cloud Dataproc?
We find that Amazon EMR and Cloudera Data Platform are the main competitors for Google Cloud Dataproc. They offer similar capabilities for big data processing using open-source tools. Azure Data Lake Store focuses on storage, so it's less directly comparable.
Yes, Google Cloud Dataproc is a legitimate service from Google Cloud. We find it's a safe and reliable platform for big data processing, used by many companies. It's backed by Google's infrastructure and integrates well with other Google Cloud services.
Is Google Cloud Dataproc legit?
Yes, Google Cloud Dataproc is a legitimate service from Google Cloud. We find it's a safe and reliable platform for big data processing, used by many companies. It's backed by Google's infrastructure and integrates well with other Google Cloud services.
Google Cloud Dataproc costs $0.01 per vCPU per hour for both Compute Engine and Google Kubernetes Engine deployments. Keep in mind that other Google Cloud service usage will incur additional costs.
How much does Google Cloud Dataproc cost?
Google Cloud Dataproc costs $0.01 per vCPU per hour for both Compute Engine and Google Kubernetes Engine deployments. Keep in mind that other Google Cloud service usage will incur additional costs.
We find that Google Cloud Dataproc's customer service receives mixed reviews. While some users praise the helpfulness of the support team, especially with critical issues, others point out the need for improved documentation and UI/UX, especially regarding IAM.
Is Google Cloud Dataproc customer service good?
We find that Google Cloud Dataproc's customer service receives mixed reviews. While some users praise the helpfulness of the support team, especially with critical issues, others point out the need for improved documentation and UI/UX, especially regarding IAM.
Reviewed by
Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.
Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.
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