AWS PrivateLink now assisted by Amazon RDS Data API

Now AWS PrivateLink can utilise Amazon RDS Data API secretly for Aurora Serverless from your Amazon VPC excluding public IPs, and traffic to travel through the Internet. Amazon RDS Data API allows you to concentrate on creating your applications keeping out all trouble of handling database connections or connection pools. HTTPS is use to transmit with your Aurora cluster by Amazon RDS Data API and is sheltered through SSL and IAM authentication. AWS PrivateLink offers individual connectivity between VPCs, AWS services, and on-premises applications, safely on the Amazon network. Now Amazon RDS Data API users can utilise private IP connectivity and security groups to fulfil their particular compliance needs. By utilising AWS PrivateLink you can run SQL statements with the help of Data API, during clarifying your internal network architecture. Now you don’t require to utilise an Internet Gateway, Network Address Translation (NAT) devices, or firewall proxies to join to RDS Data API. Create an interface VPC endpoint for Data API for Aurora Serverless in your VPC with the Amazon VPC console, SDK, or CLI to use AWS PrivateLink. Additionally, you can access the VPC endpoint from on-premises environments or from other VPCs using AWS VPN, AWS Direct Connect, or VPC Peering. This Amazon RDS Data API is accessible in US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), and Asia Pacific (Tokyo) Regions. To get further details, read documentation, or get started in the AWS Console.

Amazon Athena provides assistance for User Defined Functions (UDF)

Amazon Athena is an interactive query service which makes simple to study data straight in Amazon S3 with the help of standard SQL. You do not need to handle any infrastructure as Amazon Athena is serverless. Athena is simple to utilize. Simply point to your data in Amazon S3, specify the schema, and begin querying using standard SQL to execute ad-hoc queries and you will get results within seconds with few clicks in AWS management console. There is no necessity for complex ETL jobs to make your data for analysis with Amazon Athena. This makes it simple to SQL expertise to faster explore large-scale datasets. Now Amazon Athena offers new feature i.e. user-defined functions (UDFs), a feature which allows users to write custom scalar functions and call them in SQL queries. While Amazon Athena presents built-in functions, UDFs allow users to execute custom processing like compressing and decompressing data, redacting sensitive data, or applying customized decryption. Using Athena Query Federation SDK users can write their UDFs in Java. When a UDF is used in a SQL query submitted to Athena, it is called and performed on AWS Lambda. UDFs can be utilized in both SELECT and FILTER clauses of a SQL query. Users can call several UDFs in the same query. This new Athena UDF feature is accessible in Preview mode in the us-east-1 (N. Virginia) region. You can follow these steps to start your Preview. To know more on User Define Functions (UDF), read documentation. You can get UDF example implementations here. And to know further how to write your functions with Athena Query Federation SDK, go through this link.

Now Amazon RDS for SQL Server assists further instance sizes

Amazon RDS for SQL Server is an organised service which is created for developers who need the attributes and potentials of SQL Server for designing a new application. Besides, you can relocate current applications which use SQL Server to Amazon RDS excluding rewriting the application thoroughly. As Amazon RDS for SQL Server gives you straight access to the native potentials of the SQL Server edition you have described, your applications and tools should run smoothly. Amazon RDS for SQL Server makes it simple to set up, operate, and scale SQL Server database deployments in the cloud. Now, Amazon RDS for SQL Server db.m5 and db.r5 instance classes are obtainable in 8xlarge and 16xlarge sizes. With assistance for these new instance sizes, users who are now utilising either m4.10xlarge, m4.16xlarge, r4.8xlarge, or r4.16xlarge have an simple upgrade path to the recent generation of instances. M5 instances are the latest generation of general purpose instances and give enhanced performance across last generation M4 instances. The M5 instance group gives a balance of compute, memory, and network resources, and is a perfect suit for many database workloads. Whereas R5 instances are the latest generation of memory optimised instances which give 5% extra memory per vCPU and up to 20% boosted CPU performance over R4 instances. R5 instances are perfect fit for working memory intensive database workloads covering transaction processing, data warehousing, and analytics. To begin with, go through the AWS Management Console. And to know about pricing and regional availability, check out pricing page.

Now Amazon EC2’s R5 and T3 instance types assists Amazon RDS for SQL Server

Amazon EC2 R5 instance are the memory optimized instances for the Amazon EC2 that are perfect fit for memory concentrated applications like high performance databases, distributed web scale in-memory caches, mid-size in-memory databases, real time big data analytics, and other enterprise applications. And it helps you in the high memory demands of specific applications to boost performance and lower latency. R5 instances gives added memory per vCPU and the highest size, r5.24xlarge, offers 768 GiB of memory, permitting customers to expand and combine their workloads on couple of instances.

Amazon EC2 T3 instances are developed to execute the burstable general purpose workloads at a much lower cost. T3 instances are perfect fit for small to medium sized database workloads. T3 instances which give a baseline level of CPU performance with the potential to burst CPU utilization at any time until desired. T3 instances gives assistance for the new Intel Advanced Vector Extensions 512 (AVX-512) instruction set, providing up to 2x the FLOPS per core differentiated with the last generation T2 instances.

Now onward you can initiate R5 and T3 instance types when utilizing Amazon RDS for SQL Server. It is simple to use these new instance classes by changing your current DB instance in AWS Management Console. To get more details, go through the Amazon RDS User Guide. And to know pricing and regional availability, visit Amazon RDS pricing page.

Now Amazon Athena helps querying data in Amazon S3 Requester Pays buckets

Amazon Athena is an interactive query service which makes it simple to examine data straight in Amazon Simple Storage Service (Amazon S3) with the help of standard SQL. You can point Athena at your data stored in Amazon S3 using few clicks in the AWS Management Console and start utilizing standard SQL to execute ad-hoc queries and obtain results within seconds. There is no infrastructure to set up or manage as Athena is serverless, so you just charge for the queries you execute. Athena scales automatically—running queries simultaneously —so results are fast, even with large datasets and complex queries. Now Amazon Athena helps querying data in Amazon S3 Requester Pays buckets. Using this new launched feature, Athena workgroup administrators can configure workgroup settings to permit members to reference S3 Requester Pays buckets in queries. Once configured, the requester, rather than the bucket owner, pays for the Amazon S3 request and data transfer charges related to the query. Refer Create a Workgroup from Amazon Athena User Guide to know how to configure this setting for your workgroup. And to read further on Requester Pays buckets, click Requester Pays Buckets in the Amazon Simple Storage Service Developer Guide.

Now Amazon Athena Is Accessible In GovCloud (US-East)

Amazon Athena is an interactive query service which is easy to use and simple to study data in Amazon S3 with the help of standard SQL. Athena is serverless, in order that there is no infrastructure to handle, and you charge exclusively for the queries which you execute. Just indicate to your data in Amazon S3, specify the schema, and begin querying with the help of standard SQL. Many outcomes are offered in few seconds. There is no necessity for complex ETL (Extract, Transform, Load) jobs to make your data for analysis with Amazon Athena. This helps for everybody with SQL expertise to rapidly study large-scale datasets. Athena is merged with AWS Glue Data Catalog, permitting you to build a unified metadata repository over different services, crawl data sources to locate schemas and occupy your Catalog with new and modified table and partition definitions, and retain schema versioning. Besides, you can utilized AWS Glue’s completely organized ETL potentials to change data or convert it into columnar formats to optimize cost and better performance. Now Amazon Athena is accessible in the AWS GovCloud (US-East) region and US East (Northern Virginia, & Ohio), US West (Oregon), AWS GovCloud, Europe (Ireland, Frankfurt, & London), and Asia Pacific (Singapore, Tokyo, Sydney, Seoul, & Mumbai) regions.

Now Amazon RDS for SQL Server Offers Assistance To SQL Server Audit

Amazon RDS for SQL Server is easy to set up, operate, and scale SQL Server deployments in the cloud. You can deploy multiple editions of SQL Server (2008 R2, 2012, 2014, 2016, and 2017) containing Express, Web, Standard and Enterprise with Amazon RDS, in minutes with cost-efficient and re-sizable compute capacity. Amazon RDS lets you concentrate on application development by handling time-consuming database administration activities covering provisioning, backups, software patching, monitoring, and hardware scaling. Now, Amazon RDS for SQL Server offers assistance to SQL Server Audit which allows you build server audits, that includes server audit specifications for server level events, and database audit specifications for database level events. You can immediate access the audits on the database instance and automatically send the audit log files straight to Amazon S3. To know further on how to setup and configure SQL Server Audit, refer Amazon RDS User Guide and Amazon RDS Pricing for pricing and regional availability.