Overview

Cloudera Enterprise

Stacks126

Followers172

Votes5

Snowflake

Stacks1.2K

Followers1.2K

Votes27

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.

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Advice on Cloudera Enterprise, Snowflake

Julien

CTO at Hawk

Sep 19, 2020

Decided

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

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Detailed Comparison

Cloudera Enterprise	Snowflake
Cloudera Enterprise includes CDH, the world’s most popular open source Hadoop-based platform, as well as advanced system management and data management tools plus dedicated support and community advocacy from our world-class team of Hadoop developers and experts.	Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
Unified – one integrated system, bringing diverse users and application workloads to one pool of data on common infrastructure; no data movement required;Secure – perimeter security, authentication, granular authorization, and data protection;Governed – enterprise-grade data auditing, data lineage, and data discovery;Managed – native high-availability, fault-tolerance and self-healing storage, automated backup and disaster recovery, and advanced system and data management;Open – Apache-licensed open source to ensure your data and applications remain yours, and an open platform to connect with all of your existing investments in technology and skills	-
Statistics
Stacks 126	Stacks 1.2K
Followers 172	Followers 1.2K
Votes 5	Votes 27
Pros & Cons
Pros 1 Multicloud 1 Scalability 1 Hybrid cloud 1 Easily management 1 Cheeper	Pros 7 Public and Private Data Sharing 4 User Friendly 4 Multicloud 4 Good Performance 3 Great Documentation
Integrations
No integrations available	Python Apache Spark Node.js Looker Periscope Mode

What are some alternatives to Cloudera Enterprise, Snowflake?

Google BigQuery

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

Amazon Redshift

It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

Qubole

Qubole is a cloud based service that makes big data easy for analysts and data engineers.

Amazon EMR

It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.

Altiscale

we run Apache Hadoop for you. We not only deploy Hadoop, we monitor, manage, fix, and update it for you. Then we take it a step further: We monitor your jobs, notify you when something’s wrong with them, and can help with tuning.

Stitch

Stitch is a simple, powerful ETL service built for software developers. Stitch evolved out of RJMetrics, a widely used business intelligence platform. When RJMetrics was acquired by Magento in 2016, Stitch was launched as its own company.

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

Dremio

Dremio—the data lake engine, operationalizes your data lake storage and speeds your analytics processes with a high-performance and high-efficiency query engine while also democratizing data access for data scientists and analysts.

Airbyte

It is an open-source data integration platform that syncs data from applications, APIs & databases to data warehouses lakes & DBs.

Treasure Data

Treasure Data's Big Data as-a-Service cloud platform enables data-driven businesses to focus their precious development resources on their applications, not on mundane, time-consuming integration and operational tasks. The Treasure Data Cloud Data Warehouse service offers an affordable, quick-to-implement and easy-to-use big data option that does not require specialized IT resources, making big data analytics available to the mass market.