by INVOKE Team
Posted on December 10, 2019 at 12:00 AM
Data is everywhere! Data is key for nearly every business decision made and business success. It is not sufficient to have just the data. Great businesses use data effectively to make decisions. In a typical setup, businesses gather data into data warehouse, analyzing the data to compile information, which will be used towards developing strategies for sales, marketing, operations, KPIs, performance reports, and HR activities.
A data warehouse is a specialized type of relational database where data will be pooled into, optimized for high-performance analysis and reporting. These databases collects current and historical transactional data from many disparate operational systems associated with the business (manufacturing, finance, sales, shipping, etc.) and pulls it together in one place to guide analysis and decision-making.
Amazon Redshift is a fast, fully managed data warehouse provided by AWS Cloud, that makes it simple and cost-effective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools. With Redshift, you can start small for just $0.25 per hour with no commitments and scale out to petabytes of data for $1,000 per terabyte per year, less than a tenth the cost of traditional solutions.
Why not traditional data warehouses?
In simple terms, data warehouse is nothing but a “specialized relation database”. In traditional on-premise setting, this is a combination of databases like SQL Servers and few analytical tools on top of these servers. This set up requires time, resources to administer and manage. In addition, the financial cost associated with building, maintaining, and growing self-managed, on-premise data warehouses is enormous.
As your data grows, you have to constantly trade-off what data to load into your data warehouse and what data to archive in storage so you can manage costs, keep ETL complexity low, and deliver good performance.
Why not MPP data warehouse cluster on EC2?
Setting up MPP data warehouse using EC2 instances is not much different than traditional data warehouses. Almost all the challenges are applicable here too, except that few scalability challenges could be easily handled using techniques like AutoScaling groups.
Why AWS Redshift?
Amazon Redshift on the other hand is fully managed data warehouse. It integrates easily with existing BI tools as well as allows you to run standard SQL queries in cost effective way. Using Redshift Spectrum makes it easy to analyze large amounts of data in its native format without requiring you to load the data.
Amazon Red shift automatically handles many of the time-consuming tasks associated with managing your own data warehouse including:
Amazon Redshift billing?
Billing commences for a data warehouse cluster as soon as the data warehouse cluster is available. Billing continues until the data warehouse cluster terminates, which would occur upon deletion or in the event of instance failure.
You are billed for following components (pay for what you use):
What can be done to reduce Redshift bill?
Costs associated with running data warehouses are NOT going to be cheap unless you apply good cloud economics tactics. For example, mid size, dc2.8xlarge cluster could cost as much as $3500/month if you run it continuously.
Applying proper cost optimization techniques could lower the Redshift bill while keeping the resource usage optimal. Though not a comprehensive list, we tried to list a few different strategies that can be used to reduce the costs associated with the Redshift.
If you are looking for a solution to start and stop the RedShift cluster to save the costs, contact us . Our solution INVOKECloud could help. If not, we may be able to guide you with appropriate solution.
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