To analyze data across these sources, analysts have to learn new programming languages and data access constructs, and build complex pipelines to extract, transform and load into a data warehouse before they can easily query the data. Event and application logs are often stored in object stores such as Amazon S3. As a result, data required for analytics is often spread across relational, key-value, document, in-memory, search, graph, time-series, and ledger databases. Application developers pick a data store based on the applicationвЂ™s primary function. Running analytics on data spread across applications can be complex and time consuming. Since connectors run on Lambda, customers continue to benefit from AthenaвЂ™s serverless architecture and do not have to manage infrastructure or scale for peak demands. Additionally, using Query Federation SDK, customers can build connectors to any proprietary data source and enable Athena to run SQL queries against the data source. Customers can use these connectors to run federated SQL queries in Athena across these data sources. AWS has open-sourced Athena Data Source connectors for Amazon DynamoDB, Apache HBase, Amazon DocumentDB, Amazon Redshift, Amazon CloudWatch Logs, AWS CloudWatch Metrics, and JDBC-compliant relational data sources such MySQL, and PostgreSQL under the Apache 2.0 license.

Athena executes federated queries using Data Source Connectors that run on AWS Lambda. With Athena federated query, customers can submit a single SQL query and analyze data from multiple sources running on-premises or hosted on the cloud.

Federated Query in Amazon AthenaДЇederated query is a new Amazon Athena feature that enables data analysts, engineers, and data scientists to execute SQL queries across data stored in relational, non-relational, object, and custom data sources. Today, we are happy to announce a Public Preview of Amazon Athena support for federated queries. As the number of data stores and applications increase, running analytics across multiple data sources can become challenging. In a sense, developers are doing what they do best: dividing complex applications into smaller pieces, which allows them to choose the right tool for the right job. As Werner Vogels, CTO and VP of, said: вЂњSeldom can one database fit the needs of multiple distinct use cases.вЂќ Developers today build highly distributed applications using a multitude of purpose-built databases. Similarly, for workloads that require flexible schema for fast iterations, Amazon DocumentDB (with MongoDB compatibility) is likely a better fit. For example, for an organization building a social network, a graph database such as Amazon Neptune is likely the best fit when compared to a relational database. everything else is peachy.Organizations today use data stores that are the best fit for the applications they build. John Toups [3:17 I use Querious (mac mysql client) and Navicat (is mac/win) with no issues, except that the table-sync tools donвЂ™t work. The same issue exists using the MySQL 8 C connector and connecting to an older version of MySQL (see MySQL Bugs: #90994: libmysqlclient connecting to older MySQL 5 servers results in Bad Handshake).ДЇrom Error connecting to memsql with mysql C connector - Stack Overflow Jack [12:33 mysql changed the default authentication protocol in MySQL 8, so to connect to memsql with the MySQL 8 connector you will need to set the client configuration default-auth=mysql_native_password in some fashion, or you can use any version older than 8.

MySQL Workbench 6.3 connects, however, I have some other incompatibility issues with it when working in Amazon workspace. I tried MySQL Workbench 8.0 and I receive a handshake error. What is the best tool you recommend for connecting to MemSQL 6.0. (Ported from memsql-public-chat Slack channel)

Connect to amazon server with querious