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Cloudera Enterprise vs Snowflake: What are the differences?
Introduction
Cloudera Enterprise and Snowflake are both widely used data platforms, but there are key differences that set them apart in terms of architecture, functionality, and deployment options.
Scalability: Cloudera Enterprise offers a scalable Hadoop-based platform that can handle large volumes of data and provides distributed processing capabilities. On the other hand, Snowflake is a cloud-based data warehousing platform that is built for scalability and can dynamically scale its compute and storage resources based on workload demands.
Data Structure: Cloudera Enterprise supports a wide range of data structures and is well-suited for managing unstructured and structured data, including text and multimedia content. Snowflake, on the other hand, is designed specifically for structured data and provides robust support for SQL querying and analysis.
Deployment Model: Cloudera Enterprise can be deployed on-premises or in a hybrid cloud environment, giving organizations more flexibility in terms of data governance and compliance. Snowflake, on the other hand, is a fully managed cloud service that runs on major cloud platforms like Amazon Web Services (AWS) and Microsoft Azure.
Concurrency: Cloudera Enterprise provides multi-user concurrency through Apache Hadoop's YARN (Yet Another Resource Negotiator) technology, allowing multiple users to access and process data simultaneously. Snowflake, on the other hand, offers a unique architecture that separates compute and storage, enabling unlimited concurrency without performance degradation.
Security: Cloudera Enterprise offers comprehensive security features, including authentication, authorization, and encryption, to protect data at rest and in transit. Snowflake takes a similar approach but also provides additional security measures like secure data sharing and role-based access control (RBAC) for fine-grained access management.
Ease of Use: Cloudera Enterprise provides a unified user interface (UI) and a set of management tools that make it easier for administrators and data analysts to interact with the platform. Snowflake, on the other hand, offers a user-friendly interface and requires minimal administration, making it more accessible to a wider range of users.
In summary, Cloudera Enterprise and Snowflake differ in terms of scalability, data structure support, deployment options, concurrency capabilities, security features, and ease of use. Each platform has its strengths and is suited for different use cases and business requirements.
Cloud Data-warehouse is the centerpiece of modern Data platform. The choice of the most suitable solution is therefore fundamental.
Our benchmark was conducted over BigQuery and Snowflake. These solutions seem to match our goals but they have very different approaches.
BigQuery is notably the only 100% serverless cloud data-warehouse, which requires absolutely NO maintenance: no re-clustering, no compression, no index optimization, no storage management, no performance management. Snowflake requires to set up (paid) reclustering processes, to manage the performance allocated to each profile, etc. We can also mention Redshift, which we have eliminated because this technology requires even more ops operation.
BigQuery can therefore be set up with almost zero cost of human resources. Its on-demand pricing is particularly adapted to small workloads. 0 cost when the solution is not used, only pay for the query you're running. But quickly the use of slots (with monthly or per-minute commitment) will drastically reduce the cost of use. We've reduced by 10 the cost of our nightly batches by using flex slots.
Finally, a major advantage of BigQuery is its almost perfect integration with Google Cloud Platform services: Cloud functions, Dataflow, Data Studio, etc.
BigQuery is still evolving very quickly. The next milestone, BigQuery Omni, will allow to run queries over data stored in an external Cloud platform (Amazon S3 for example). It will be a major breakthrough in the history of cloud data-warehouses. Omni will compensate a weakness of BigQuery: transferring data in near real time from S3 to BQ is not easy today. It was even simpler to implement via Snowflake's Snowpipe solution.
We also plan to use the Machine Learning features built into BigQuery to accelerate our deployment of Data-Science-based projects. An opportunity only offered by the BigQuery solution
Pros of Cloudera Enterprise
- Easily management1
- Cheeper1
Pros of Snowflake
- Public and Private Data Sharing7
- Multicloud4
- Good Performance4
- User Friendly4
- Great Documentation3
- Serverless2
- Economical1
- Usage based billing1
- Innovative1
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