With data comes a great storage responsibility, thereby making data warehousing an integral concept. The market is flooded with options, end users are spoilt for options. Each data warehousing element offers its own set of unique features, which makes each platform worth consideration.
Without going into the wider set of possibilities, let’s limit our discussion to the top two market leaders: Snowflake vs Redshift.
The Multi-Talented Snowflake
Thinking about moving to the cloud? Good idea—you can back it up with Snowflake’s Cloud Data Platform.
Snowflake is an enterprise-ready cloud data warehouse (CDW) that offers simplicity without sacrificing features and capabilities. It provides options to enterprises to scale up and down as needed.
Snowflake is built on top of Amazon Web Services (AWS) and doesn’t have the hassle of on-premise hardware or software management. Rest assured, there’s no software or hardware to install, configure, or manage, which makes it ideal for organizations looking to move away from on-prem servers and data resources to the cloud.
Additionally, Snowflake can be regarded as a software-as-a-service (SaaS) tool, and it provides exceptional insight into structured and nested data. Its fast paced competency, computing prowess, and flexibility allow it to work seamlessly in conjunction with AWS. It uses Amazon’s Elastic Container Service (EC2) and Simple Storage Service (S3), thereby providing fast data analytics,nd a controlled data access to AWS users.
Amazon’s Redshift is hard to ignore
Unlike its competitors, Amazon’s Redshift is a fully-managed data warehouse, maintained and owned by AWS. You can store petabytes of data within Amazon’s S3 buckets. All the stored data can be queried via Amazon Redshift Spectrum’s SQL services.
This saves bothersome data transformation steps, thereby enabling fast query optimization, scaling, and quick extraction methodologies. Redshift has been designed for the large-scale data requirements of organizations. For this reason, it’s imperative for users to perform large-scale data migrations via Redshift to exemplify their usage needs.
Snowflake vs Redshift: What’s common?
Let’s look into some common features, which makes the two tools’ winners in their own respective fields:
- Both use SQL for querying stored data. Snowflake uses SnowSQL, while Redshift offers SQL through its Amazon Redshift Spectrum suite of services. Each of these tools can further be aligned with business intelligence and other available ETL tools.
- Both can handle large-scale parallel processing functionality for enhanced user querying experiences.
- Both are designed for efficient and intelligent data management. If you are looking to make well-informed, data-driven decisions, both Snowflake and Redshift will work for you.
- Both are column-oriented, giving the underlying data a well-maintained structure. This is the essence of an effectively designed database.
Snowflake vs Redshift: What’s different?
There are more differences than similarities when examining Snowflake vs Redshift. In fact, the differences between the tools tend to cause users to take sides, when it comes to that.
The decision to choose one over the other is often subjective and need-driven, so be sure to browse this section to be a better judge of which tool suits your data needs.
1. Performance maketh a tool.
In the technology world, the performance of a tool is most important. Although scalability is an important aspect, it is considered nothing but a vanity feature. Let’s face it—most companies don’t need exorbitant amounts of storage space and computing capabilities.
What’s important, on the other hand, is the level of complexity handling and the ability to push results, as and when needed.
When you are querying data—either for data-backed decisions or machine learning—chances are that you’re making use of different data sources that need to be joined with each other to arrive at the final dataset.
Which tool can handle such complexity with the flick of a button and return results faster than the blink of an eye? To be honest, both rank equally in terms of managing complex queries and joins.
However, Snowflake pulls forward in the performance category, mostly due to its automated performance optimization. The tool is equipped to automatically adjust your workload to increase performance.
Redshift, on the other hand, is more manual in terms of adjustment, which might put it on the lower pedestal for a few users.
2. Pricing is all about money well spent.
When an organization looks for fast, reliable options, they often look at pricing. With such fierce competitors in the running, price is usually a tie-breaker.
Both Redshift and Snowflake are priced by the hour, but that’s where the similarities end.
Redshift is an on-demand service, and each node usage is priced per hour. Additional cloud services, like Amazon Managed Storage, are priced separately.
One positive of this model is that an organization can build a storage system that suits their storage needs. However, this might involve a lot of time and effort to piece it all together, so that’s a downside.
Snowflake’s pricing model is a different ball game altogether. First, it offers a set of predefined packages:
- Business Critical
- Virtual Private Snowflake
These packages vary based on their cloud services and encryption levels, materialized views, and compliance provisions. Additionally, Snowflake does not offer a per-hour usage plan—it’s based on a credit system. Depending on your warehouse size, your credit limits would range between one to 128 credits per hour.
One credit is equal to one server, meaning that different warehouses would employ different numbers of servers, which would determine the total usage credits.
The pricing model might prove to be another feather in Snowflake’s cap, as they are easier to understand and employ within an organization.
3. Security measures secure the unsecured.
Security is an important aspect and relies heavily on the cloud provider. Both Snowflake and Redshift handle the issue of security differently. Snowflake, on one hand, offers enterprise-grade encryption, applicable for in-transit data.
Some additional measures, like annual rekeying and customer-managed keys, are a part of the Enterprise and Business Critical pricing packages.
On the other hand, Redshift offers an option to encrypt at-rest data, with no frills attached. Since data security is a prime concern for many enterprises, it offers AWS Key Manage Services (KMS) at affordable costs.
You can use KMS to create customer-managed keys, at just a nominal charge of $1/month. Subsequently, Redshift also offers affordable packages for data in transit.
4. Scaling up and down, or maybe not at all?
Why does an enterprise move its data to the cloud? Apart from storage and customizable pricing plans, there’s a lot more than meets the eye. Scalability is another major factor that influences enterprise decisions to move to the cloud.
Redshift is a stubborn tool, which does not offer scalability as an optional feature. Redshift adds and removes new nodes from every cluster, which makes auto-scaling range from minutes to sometimes hours. It all depends on the complexity and the size of the data request.
Snowflake, on the other hand, auto-scales without delays, ranging from seconds to minutes only. Data is stored separately, and not within clusters, which enables uninterrupted data computing and seamless scaling from one user to another.
Deciding Between Snowflake vs Redshift
|Choose Snowflake if…||Choose Redshift if…|
|You have low query load computing.||You like to use AWS services.|
|Your data requirements need to be scaled up and down regularly.||You have high query load computing.|
|You want an automated solution that requires little to almost no maintenance.||Your underlying data is neatly structured.|
|Your organization can commit to busy clusters for a year at least.|
Data warehousing is an important aspect that can’t be overlooked during the data storage process. Since data is confidential, it needs to be stored with appropriate encryption levels but made available when the need arises.
For this very reason, enterprises tend to look at various parameters while deciding on the right cloud service provider for their organization. Considering Snowflake vs Redshift, you can’t go wrong with either. Both are standout options for a data warehouse. Be sure to understand your organization’s needs before deciding as this may make one option a better fit than the other.
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