It was even simpler to implement via Snowflake's Snowpipe solution. Omni will compensate a weakness of BigQuery: transferring data in near real time from S3 to BQ is not easy today. It will be a major breakthrough in the history of cloud data-warehouses. The next milestone, BigQuery Omni, will allow to run queries over data stored in an external Cloud platform (Amazon S3 for example). We've reduced by 10 the cost of our nightly batches by using flex slots.įinally, a major advantage of BigQuery is its almost perfect integration with Google Cloud Platform services: Cloud functions, Dataflow, Data Studio, etc.īigQuery is still evolving very quickly. 0 cost when the solution is not used, only pay for the query you're running.īut quickly the use of slots (with monthly or per-minute commitment) will drastically reduce the cost of use. Its on-demand pricing is particularly adapted to small workloads. We can also mention Redshift, which we have eliminated because this technology requires even more ops operation.īigQuery can therefore be set up with almost zero cost of human resources. Snowflake requires to set up (paid) reclustering processes, to manage the performance allocated to each profile, etc. These solutions seem to match our goals but they have very different approaches.īigQuery 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. Our benchmark was conducted over BigQuery and Snowflake. The choice of the most suitable solution is therefore fundamental. See moreĬloud Data-warehouse is the centerpiece of modern Data platform. Regardless, you'd certainly only keep high-level records, meta data in Database, and the actual files, most-likely in S3, so that you can keep all options open in terms of what you'll do with them. Other database services exist, I'd recommend you also explore Dynamo DB. I personally would recommend MySQL (latest version available), as the official tooling for it (MySQL Workbench) is great, stable, and moreover free. As far as which database to chose, you'll have the choice between Postgresql, MySQL, Maria DB, SQL Server. Doing this on your own would either be risky, inefficient, or you might just give up. Such managed services easily allow you to apply new security patches and upgrades, set up backups, replication. Aurora would be my preferred choice given the benefits it offers, storage optimizations it comes with. If you are on AWS, thet have different offerings for database services. Don't spin up your own MySQL installation on your own Linux box. Hi Erin! First of all, you'd probably want to go with a managed service. Microsoft SQL Server has a broader approval, being mentioned in 478 company stacks & 443 developers stacks compared to Amazon Redshift, which is listed in 269 company stacks and 67 developer stacks. Stack Exchange, Microsoft, and MIT are some of the popular companies that use Microsoft SQL Server, whereas Amazon Redshift is used by Lyft, Coursera, and 9GAG. "Data Warehousing" is the primary reason why developers consider Amazon Redshift over the competitors, whereas "Reliable and easy to use" was stated as the key factor in picking Microsoft SQL Server. Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.Īmazon Redshift can be classified as a tool in the "Big Data as a Service" category, while Microsoft SQL Server is grouped under "Databases". What is Microsoft SQL Server? A relational database management system developed by Microsoft. It is optimized for datasets 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. Redshift makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. What is Amazon Redshift? Fast, fully managed, petabyte-scale data warehouse service. Amazon Redshift vs Microsoft SQL Server: What are the differences?
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