It acknowledges that Simform can skillfully execute new RDS implementations and database migrations and build RDS-compatible tools for its customers.īeing an RDS Service Delivery Partner enables Simform to enhance performance, security, and monitoring for its customers across seven database engines supported by RDS, including Amazon Aurora MySQL, Aurora PostgreSQL, PostgreSQL, MySQL, MariaDB, Oracle, SQL Server. It recognizes Simform for delivering cost-efficient and scalable solutions to ease management of all complex, administrative, and time-consuming tasks related to RDS. The Amazon RDS Service Delivery Program (SDP) is accredited to APN partners for following best practices with Amazon RDS. Maintaining and querying the data in DynamoDB is also easier.Simform Achieves Amazon RDS Service Delivery Program (SDP) Partnership Storage pricing is similar to S3, query pricing also. Today, with "On-Demand" pricing, I would definitively use DynamoDB for this tool. Having to provision (and pay for) a fixed throughput was too expensive. When S3-Select came out, DynamoDB didn't have an "On-Demand" pricing. Cloudfront is used as a database-cache layer to avoid having to query twice for the same IP.The data files are sharded by primary key to reduce the scan size.I made some tweaks from the above example: You can read more about it in my blog or install it from my Github repo (works with GeoIP2 and GeoLite2 databases). This helps on the administrative side by managing updates in only one place, remove boot up scripts while autoscaling, and also it allows other processes and services to use this data (ETL, logging, lambda. I wanted to replace the locally installed databases on each server by an HTTP service. When S3-Select came out, I decided to use the above concept to create a Serverless GeoIP API using Maxmind's GeoIP2 databases. The ability to update content with more traditional non-database tools, allows a wider range of peoples to curate and maintain the data. Keep in mind, that the read speed is far below what you can achieve with a real databases on SSD, so don't use this for anything time sensitive. Consider it as your read-only slave database. But it works very well for single large datasets on which you need to retrieve a small chunk. But needed to return only 1KB (~0.3% of the total file).Ĭonsidering S3 as a Database is surely far fetched. S3-Select had to scan the whole compressed file and needed to process the uncompressed content. SharedIniFileCredentials ()Įnter fullscreen mode Exit fullscreen mode Also available in most of the SDK's.įor the CLI, you find it under aws s3api select-object-content.Ĭonst AWS = require ( ' aws-sdk ' ) var credentials = new AWS. The API allowing to query a file's content is SelectObjectContent. With CSV and JSON the whole file needs to be scanned. Being a columnar format, the amount of data scanned is greatly reduced, since only the needed columns are used. On the query side, Parquet is the clear winner. Obviously, this becomes less of a factor once compressed. With CSV and Parquet you define your attributes only once. With all the attributes repeated, JSON is the heaviest format. Using a spreadsheet software helps for CSV. For CSV and Parquet, you need to alter each entry with the new field. Schema alterations are straight forward in JSON, since every entry carries it's own schema. Parquet needs some additional skills and tools. The format to use mainly depends on your production capabilities and query needs.īeing text formats, CSV and JSON a very easy to produce (code, spreadsheets. S3-Select stills needs to scan the whole file (you pay for that), but you gain on the processing side.Įach format has it's pros and cons. Therefore reducing network transfer, storage and memory on the processing side, which translates into cost reduction. Instead of loading a large file, you retrieve only the useful content. All you need is an S3 PutObject access (Console, CLI, SDK, SFTP. But this comes with a benefit: updating the data becomes very easy.You can't update a single entry, you need to replace the whole file.Supported compressions are GZIP or BZIP2.The content of the file must be in JSON, CSV or Apache Parquet.Data needs to be in a single file and can't be grouped under a prefix. You can think of it as a single table-database. S3 select allows to retrieve partial content from a single key in S3 using SQL. During re:Invent 2017, AWS announced a new feature for S3: s3-select, which went GA in April 2018.
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