{"id":311,"date":"2021-03-29T18:02:04","date_gmt":"2021-03-29T16:02:04","guid":{"rendered":"https:\/\/stage.usercentrics.com\/?post_type=knowledge&#038;p=8186"},"modified":"2025-06-24T12:54:16","modified_gmt":"2025-06-24T10:54:16","slug":"deal-with-google-bigquery","status":"publish","type":"knowledge","link":"https:\/\/usercentrics.com\/us\/knowledge-hub\/deal-with-google-bigquery\/","title":{"rendered":"What&#8217;s the deal with Google BigQuery, and what does it cost?"},"content":{"rendered":"\n\n<p><span style=\"font-weight: 400;\">The purpose of this article is to give you a rough overview of BigQuery and a few insights into its pricing factors. Even though you might want to start immediately \u2014 trust me, I really understand you here \u2014 it is always recommended first to check out the pricing of the service one wants to use to verify that it fits your needs. I mean, none of us wants to suddenly wake up and see a $100k <\/span><span style=\"font-weight: 400;\">bill from his cloud provider since we didn&#8217;t understand the pricing model, right? Unfortunately, there are more than enough actual cases where this happened to people.<\/span><\/p>\n\n\n<h2 class=\"wp-block-heading\">BigQuery in a nutshell<\/h2>\n<p><span style=\"font-weight: 400;\">Google BigQuery is a serverless, highly scalable, and cost-effective, fully managed enterprise data warehouse used for easy and fast analysis of petabytes of data and billions of rows using ANSI SQL.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">What does that mean for you?<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">No server maintenance or configuration<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Automatic scaling to infinity<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">The only responsibility is the creation\/maintenance of tables and data<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">In case you are familiar with the very popular ANSI SQL, you are already ready to start<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">\u2192 It&#8217;s easy to get started.<\/span><\/p>\n<p><b>In super simple terms<\/b><\/p>\n<p><span style=\"font-weight: 400;\">With BigQuery, Google offers a managed relational database with a pay-as-you-go model, only billing you for its service&#8217;s actual usage.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Furthermore, one additional advantage of BigQuery is that it integrates effortlessly with other GCP products. Also, you can easily visualize data from BigQuery in Google&#8217;s Data Studio.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">You can do the whole interaction with BigQuery in several ways.<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Using the GCP console<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Using CLI commands<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Client libraries for the programming language of your choice<\/span><\/li>\n<\/ul>\n\n\n<h2 class=\"wp-block-heading\">The costs<\/h2>\n<p><span style=\"font-weight: 400;\">Starting directly with the costs might be a bit unusual. But especially in the cloud environment, costs are an essential factor and already helps in many cases if certain cloud technologies are even feasible for the intended use case or the use case will make costs explode.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Using BigQuery, you must factor in three different cost drivers.<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Storage costs (active vs long-term)<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Insert costs (batch vs streaming)<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Query costs (pay-as-you-go vs flat-rate pricing)<\/span><\/li>\n<\/ul>\n<p><b>Storage costs<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Typical for cloud services, Google bills you for the actual storage you use in BigQuery. Especially since there is a 10 GB free storage per month, you won&#8217;t have to fear any high bill when you want to start slowly with BigQuery. Google will charge any additional active storage in the case of multi-region US or EU by $0.020 per GB per month.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Now super &#8220;smart&#8221; people could say:\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">&#8220;Okay, then I will load my petabytes of data to BigQuery, do all my analyzing stuff, and then I delete it, and then I pay almost nothing. Since I don&#8217;t have any data there at the end of the month!&#8221;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Excellent idea, won&#8217;t work. Of course, Google is super intelligent and similar to all other serverless products; they check your storage usage in BigQuery every second and granular bill by second.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Compared to active storage, long-term storage, on the other hand, costs only 50% of the active one, so $0.010 per GB per month, as of today. It&#8217;s always recommended to structure one&#8217;s data for long-term storage to reduce costs.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">But what is long-term storage in the first place, and how can one get it?<\/span><\/p>\n<p><b>Long-term storage<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Long-term storage in BigQuery is nothing one can book at GCP. It is something that Google automatically categorizes as such, depending on a simple factor.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">When a table or table partition \u2014 we will handle table partitions in a later article \u2014 isn&#8217;t modified for 90 consecutive days, Google will automatically categorize it as long-term storage.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The actions defined as &#8220;modification&#8221; are pretty straightforward. Every write\/insert of data into the table is a modification and reset the 90 days timer. Actions like querying, copying, or exporting data from the table and updating the table resource \u2014 not the data in it! \u2014 are considered &#8220;non-modifications&#8221; and, as such, won&#8217;t reset the timer.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Moreover, an important aspect to mention here is that long-term storage doesn&#8217;t imply any performance degradation, durability, availability, or other functionality. Google only charges you less for it.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">We will discuss an approach to structure data to use the long-term storage functionality in detail in a later article.<\/span><\/p>\n<p><b>Ways to insert data and its costs<\/b><\/p>\n<p><span style=\"font-weight: 400;\">In BigQuery, there are two possible ways to load data into your tables.<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Batch loading<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Streaming<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">With batch loading, you are using one big batch operation to load all the data into your BigQuery tables. Typical use cases here are importing CSV files, an external database, or a fixed set of log files.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">On the other hand, the streaming approach lets you insert one record or small batches of records dynamically in your BigQuery tables. A typical use case here is when your servers directly write logs or user interactions \u2014 e.g., tracking \u2014 straight to your BigQuery without a step in-between.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Using the shared slot pool with on-demand-pricing batch loading is free of charge. But streaming inserts aren&#8217;t free and are charged $0.010 per 200 MB (multi-region US or EU). Google treats each row you write with a minimum of 1 KB in size.<\/span><\/p>\n<p><b>Query costs<\/b><\/p>\n<p><span style=\"font-weight: 400;\">The third cost source of BigQuery is when you query your data. With on-demand pricing, Google bills $5.00 per TB \u2014 $0.000000000005 per byte \u2014 processed by your queries, even though there is a free tier of 1 TB per month.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Google calculates the total size of the charged data query costs by the columns selected and its column data type times the found values.<\/span><\/p>\n<p><strong>Example:<\/strong><\/p>\n<p><span style=\"font-weight: 400;\">Imagine the following table being the BigQuery table you want to run a query against, while the first row outlines the data types for the individual column. This example doesn&#8217;t show the column names.<\/span><\/p>\n<div id=\"attachment_8187\" style=\"width: 387px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-8187\" class=\"wp-image-8187 size-full\" src=\"https:\/\/usercentrics.com\/wp-content\/uploads\/sites\/7\/2021\/03\/IMAGE_TYPE_TABLE-1.png\" alt=\"TYPE_TABLE\" width=\"377\" height=\"117\" \/><p id=\"caption-attachment-8187\" class=\"wp-caption-text\">TYPE TABLE<\/p><\/div>\n<p><span style=\"font-weight: 400;\">As you can see in the above table, an <\/span><i><span style=\"font-weight: 400;\">INT64<\/span><\/i><span style=\"font-weight: 400;\"> and <\/span><i><span style=\"font-weight: 400;\">FLOAT64<\/span><\/i><span style=\"font-weight: 400;\"> data type count as 8 bytes, the <\/span><i><span style=\"font-weight: 400;\">BOOL<\/span><\/i><span style=\"font-weight: 400;\"> one as 2. Besides these, Google treats <\/span><i><span style=\"font-weight: 400;\">NULL<\/span><\/i><span style=\"font-weight: 400;\"> values as 0 bytes, so there are no additional costs for <\/span><i><span style=\"font-weight: 400;\">NULL<\/span><\/i><span style=\"font-weight: 400;\"> values. To see the complete list of types and their billed size, you can visit the official <\/span><a href=\"https:\/\/cloud.google.com\/bigquery\/pricing#data\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">BigQuery Pricing Docs<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">So put together, if you query all the columns in the above table, it would cost you:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Row #1: 2x 8 bytes, 1x 2 bytes<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Row #2: 1x 8 bytes, 1x 0 bytes, 1x 2 bytes<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Total: 28 bytes (\u2192 $0.00000000014)<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Of course, a total of 28 bytes is super low, and you can run endless queries till you reach the first free 1 TB, but usually, a table would be bigger than just two rows and three columns. Besides that, it&#8217;s also important to mention that regardless of how big the table is, Google defines a minimum of 10 MB per query.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Even if the table is only 5 MB \u2014 or 28 bytes in the above example \u2014 using 10 MB as a minimum cost per query results in a minimum of $0.00005 per query, which is still pretty low.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Another hack some people might think of is to use &#8220;LIMIT&#8221; in the SQL query so that BigQuery will return fewer data. Even though that will not affect the billing because BigQuery bills the bytes read in the query and not by the results returned.<\/span><\/p>\n\n\n<div id=\"uc-cta_69e358acae0f8\" class=\"uc-cta uc-cta--illustration uc-cta--primary uc-ctx--blue\">\n    <div class=\"uc-cta__inner container\">\n        <div class=\"uc-cta__content\">\n                            <div class=\"uc-cta__label like-label-m\">Whitepaper<\/div>\n                                        <div class=\"uc-cta__heading no-default-margin\">Marketing is driven by ever-changing technologies and data streams &#8211; ensure your website brings them together seamlessly <\/div>\n                                        <div class=\"uc-cta__description\">\n                    <p>Check out our whitepaper to learn more about strategies to optimize opt-ins while maintaining data compliance. <\/p>\n                <\/div>\n                                                    <div class=\"uc-cta__buttons\">\n                    <a id=\"f98162b1-90ff-4d57-b666-ad95afff86c6\" class=\"uc-button uc-button-size-m uc-button-contained  no-default-link-decoration\" href=\"https:\/\/usercentrics.com\/resources\/gdpr-checklist\/\" target=\"\"><span>Download now<\/span><\/a>                <\/div>\n                                            <\/div>\n                            <div class=\"uc-cta__section\">\n                                                                    <div class=\"uc-cta__section__img-wrapper\">\n                                <img loading=\"lazy\" decoding=\"async\" width=\"1\" height=\"1\" src=\"https:\/\/usercentrics.com\/us\/wp-content\/uploads\/sites\/7\/2021\/04\/Checklist.png\" class=\"attachment-large size-large\" alt=\"Icon_Checklist\" \/>                            <\/div>\n                                                            <\/div>\n            <\/div>\n<\/div>\n    <script type=\"module\">\n        new Uc_Cta(document.getElementById(\"uc-cta_69e358acae0f8\"));\n    <\/script>\n\n\n<h2 class=\"wp-block-heading\">Going big<\/h2>\n<p><span style=\"font-weight: 400;\">If you get huge and plan to store more than 1 PB of data in BigQuery, Google suggests reaching out to their sales representative, so there is for sure a way to get the rates down even further.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">But what do I mean by &#8220;get huge&#8221;? Let&#8217;s have a quick look at GCP&#8217;s pricing calculator, and let&#8217;s see what 1 PB of data (active storage) would cost with BigQuer:<\/span><\/p>\n<div id=\"attachment_8188\" style=\"width: 478px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-8188\" class=\"wp-image-8188 size-full\" src=\"https:\/\/usercentrics.com\/wp-content\/uploads\/sites\/7\/2021\/03\/IMAGE_PRICING_CALCULATOR-1.png\" alt=\"PRICING_CALCULATOR\" width=\"468\" height=\"511\" \/><p id=\"caption-attachment-8188\" class=\"wp-caption-text\">PRICING CALCULATOR<\/p><\/div>\n<p><span style=\"font-weight: 400;\">As you can see, only the storage without any inserts or queries would cost over $20k per month! Furthermore, I think that is high enough to negotiate the pricing with Google, especially since BigQuery will most likely not be your only high cost on GCP in this case.<\/span><\/p>\n\n\n<div class=\"uc-notice\">\n    <div class=\"uc-notice__icon\">\n        <svg width=\"24\" height=\"24\" viewBox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<path d=\"M11.8177 17.0093C12.1011 17.0093 12.3386 16.9134 12.5302 16.7218C12.7219 16.5301 12.8177 16.2926 12.8177 16.0093C12.8177 15.7259 12.7219 15.4884 12.5302 15.2968C12.3386 15.1051 12.1011 15.0093 11.8177 15.0093C11.5344 15.0093 11.2969 15.1051 11.1052 15.2968C10.9136 15.4884 10.8177 15.7259 10.8177 16.0093C10.8177 16.2926 10.9136 16.5301 11.1052 16.7218C11.2969 16.9134 11.5344 17.0093 11.8177 17.0093ZM10.8177 13.0093H12.8177V7.00928H10.8177V13.0093ZM11.8177 22.0093C10.4344 22.0093 9.13442 21.7468 7.91775 21.2218C6.70108 20.6968 5.64275 19.9843 4.74275 19.0843C3.84275 18.1843 3.13025 17.1259 2.60525 15.9093C2.08025 14.6926 1.81775 13.3926 1.81775 12.0093C1.81775 10.6259 2.08025 9.32594 2.60525 8.10928C3.13025 6.89261 3.84275 5.83428 4.74275 4.93428C5.64275 4.03428 6.70108 3.32178 7.91775 2.79678C9.13442 2.27178 10.4344 2.00928 11.8177 2.00928C13.2011 2.00928 14.5011 2.27178 15.7177 2.79678C16.9344 3.32178 17.9928 4.03428 18.8927 4.93428C19.7927 5.83428 20.5052 6.89261 21.0302 8.10928C21.5552 9.32594 21.8177 10.6259 21.8177 12.0093C21.8177 13.3926 21.5552 14.6926 21.0302 15.9093C20.5052 17.1259 19.7927 18.1843 18.8927 19.0843C17.9928 19.9843 16.9344 20.6968 15.7177 21.2218C14.5011 21.7468 13.2011 22.0093 11.8177 22.0093Z\" fill=\"black\"\/>\n<\/svg>\n    <\/div>\n    <div class=\"uc-notice__content\">\n                <div class=\"like-h4 no-default-margin\">What&#8217;s next?<\/div>\n<p> <span style=\"font-weight: 400;\">In the following articles, we will see how to get started with Google&#8217;s BigQuery, based on an empty GCP project where we programmatically create new tables, fill them with our data and run queries against them.<\/span><\/p>\n            <\/div>\n<\/div>\n\n\n\n\n<h2 class=\"wp-block-heading\">Author<\/h2>\n<p><strong>Pascal Zwikirsch<\/strong><\/p>\n<p>Pascal Zwikirsch is a Technical Team Lead at Usercentrics. He manages a cross-functional team of several frontend and backend developers while providing a seamless connection between the technical world and the product managers and stakeholders.<\/p>\n<p>Pascal was a former frontend developer for several years and now specializes in backend services, cloud architectures, and DevOps principles<b data-stringify-type=\"bold\">.<\/b>\u00a0He experienced both worlds in detail.<b data-stringify-type=\"bold\">\u00a0<\/b>This experience and the collaboration with product managers made him capable of constructing full-fledged scalable software.<\/p>\n<p>Besides his job as a Team Lead of the B2B developer team, he likes to share his in-depth knowledge and insights in articles he creates as an independent technical writer.<\/p>\n<p><span style=\"font-weight: 400;\">If you have any questions or additions, feel free to hit me up on <\/span><a href=\"https:\/\/www.linkedin.com\/in\/pascal-zwikirsch-3a95a1177\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">LinkedIn<\/span><\/a><span style=\"font-weight: 400;\"> to get in contact with me.\u00a0<\/span><\/p>\n\n\n","protected":false},"excerpt":{"rendered":"<p>The purpose of this article is to give you a rough overview of BigQuery and a few insights into its pricing factors. Even though you might want to start immediately \u2014 trust me, I really understand you here \u2014 it is always recommended first to check out the pricing of the service one wants to use to verify that it fits your needs. I mean, none of us wants to suddenly wake up and see a $100k bill from his cloud provider since we didn&#8217;t understand the pricing model, right? Unfortunately, there are more than enough actual cases where this happened to people.<\/p>\n","protected":false},"featured_media":2080,"template":"","meta":{"_acf_changed":false,"editor_notices":[],"footnotes":""},"tags":[],"magazine_issue":[],"magazine_tag":[],"resource_tag":[14,13],"class_list":["post-311","knowledge","type-knowledge","status-publish","has-post-thumbnail","hentry","resource_tag-privacy","resource_tag-regulations"],"acf":[],"yoast_head":"<title>What&#039;s the deal with Google BigQuery, and what does it cost?<\/title>\n<meta name=\"description\" content=\"With BigQuery, Google offers a managed relational database with a pay-as-you-go model, only billing you for its service&#039;s actual usage.\" \/>\n<meta name=\"robots\" content=\"noindex, follow\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"What&#039;s the deal with Google BigQuery, and what does it cost?\" \/>\n<meta property=\"og:description\" content=\"With BigQuery, Google offers a managed relational database with a pay-as-you-go model, only billing you for its service&#039;s actual usage.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/usercentrics.com\/us\/knowledge-hub\/deal-with-google-bigquery\/\" \/>\n<meta property=\"og:site_name\" content=\"Usercentrics - 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