Looking for BigQuery pricing? Find out what the cost of BigQuery is for your company here in case you are looking for a serverless data analytics platform.
What Is BigQuery?
BigQuery is a serverless, multi-cloud data warehouse that streamlines your process of working with all types of data in order to gain business insights more quickly. With BigQuery, you can scale analytics effectively, share rich data experiences, train and deploy machine learning models with a simple SQL interface, simplify data integration, simplify data integration, simplify data security, scale analytics, share rich data experiences, and make your organization’s operations more data-driven.
Using BigQuery, businesses of all sizes can conduct a large-scale analysis of their data. It is a cloud-first, serverless warehouse that is fully managed by the company. It executes even the most complex queries in a matter of seconds, regardless of the size of the data. In order to get more value out of their data, organizations of all sizes can use BigQuery to break down data silos.
BigQuery offers a number of benefits, as well as strategies and tools for optimizing its costs. Understanding BigQuery pricing options is crucial to exploring BigQuery-enabled data strategies, as well as which strategies will work best for your unique use case.
BigQuery pricing has two main models. Analyzing and querying are handled by separate programs.
With flat-rate pricing, you purchase slots, which are virtual CPUs. In on-demand pricing, each query is charged based on the number of bytes it processes. It is possible to combine both of these models according to your needs. As a result, you do not have to worry about moving data between systems. Under flare-rate pricing, $10,000 would secure you 500 slots. A maximum of 500 virtual CPUs will be allocated to your queries at any given time. The BigQuery on-demand pricing model charges you based on the time you spend using the tool. Your costs will increase as you scan more bytes.
BigQuery Pricing Plans
Storage and analysis are two major factors that influence BigQuery pricing depends on. The storage costs that BigQuery charges are the costs associated with storing your business data. Storage fees are charged both for active and long-term storage.
- Active storage: A list of tables and partitions that have been updated within 90 days. Currently, BigQuery charges $0.02 per GB of data stored per month.
- Long-term storage: Tables and partitions that have not been updated for 90 days. After 90 days, monthly storage costs drop by 50%, from $0.02 to $0.01 per month.
There is no difference between active and long-term storage in terms of performance, security, and availability.
BigQuery Enterprise Pricing
BigQuery pricing is flat-rate and is available for enterprise-level customers who prefer to pay a constant month-to-month price, rather than paying on-demand prices for creating, evaluating, inspecting, and predicting models. Customers can train their BigQuery ML models using reservations. As part of the BigQuery flat-rate price, you will also receive BigQuery machine-learning costs.
BigQuery Product Comparison
During the first 90 days, new customers receive $300 in free BigQuery credits. The free usage per month includes 10 GB of storage and up to 1 TB of queries, which are not deducted from the credits of the customer. Storage of data, streaming inserts, and querying data is charged by BigQuery, but loading and exporting data are free. Monthly storage rates are $0.02 per GB, while long-term storage rates are $0.01 per GB, per month. Streaming inserts are $0.01 per 200 MB.
How Much Does BigQuery Cost?
BigQuery pricing is not one-size-fits-all, so you can easily find the best option for your needs. A new pricing structure for BigQuery has been introduced by Google in recent months called BigQuery flex slots. BigQuery pricing allows users to buy slots for 60 seconds at a time using this short-term option. When users scale up and down rapidly, they can take advantage of flex slots to control costs and predict outcomes.
If BigQuery Pricing is Too High, Check Out These BigQuery Alternatives
These are the top BigQuery Alternatives
- Y42: In the field of data operations, Y42 has built the first fully managed Cloud for Modern DataOps. Data pipelines can be built easily on top of Google BigQuery or Snowflake cloud data warehouses with this tool
- Adverity: With Adverity, companies can build a single source of truth about marketing and business performance by fully automating data integration from all data sources.