A JDBC driver is a Java library file (.jar) that enables Java applications — including DbSchema — to communicate with a database over a standard API. The driver translates generic JDBC calls into the network protocol understood by Amazon Timestream, so you never have to write low-level socket code. Drivers are typically distributed by the database vendor or as open-source projects.
Every JDBC driver identifies the target database through a connection URL. The URL encodes the hostname, port, database name, and any driver-specific parameters as a single string. The exact syntax varies per driver — the details for Amazon Timestream are listed in the section below.
Amazon Timestream is a fast, scalable, and serverless time-series database service built for IoT and operational applications on AWS. It automatically scales to adjust capacity and performance, storing and analyzing trillions of events per day. Timestream's built-in time-series analytics functions make it straightforward to query measures and dimensions across time windows.
Requires AWS access key ID, secret access key, and region specification. The default port is 443 (HTTPS). Credentials can also be supplied via IAM roles or environment variables, making it straightforward to integrate with AWS-managed infrastructure without hardcoding secrets.
DbSchema connects to Amazon Timestream using the JDBC driver, allowing you to browse time-series tables, visualize their measures and dimensions, and run SQL queries against IoT and telemetry datasets. Use the SQL editor to write time-series analytics with functions like ago() and bin().
Have connection issues? Contact the DbSchema team for help.
Once the JDBC driver is configured, DbSchema connects to your Amazon Timestream database and gives you a full graphical workbench — no command-line required. Available as a free Community Edition and a full-featured PRO Edition. No registration needed to get started.
Reverse-engineer your Amazon Timestream schema into a drag-and-drop ER diagram. Arrange tables visually, add new columns, define foreign keys, and let DbSchema generate the DDL — all without writing SQL by hand.
Compose Amazon Timestream queries by clicking on tables and columns — no SQL knowledge required. Add joins, filters, groupings, and aggregations through a point-and-click interface, then copy the generated SQL or run it directly against the live database.
Browse Amazon Timestream table data and follow foreign key relationships across tables in a single view. Edit cells inline, filter rows, and paginate through large datasets — all without leaving the explorer.
Compare your Amazon Timestream schema across development, staging, and production environments. DbSchema generates the exact ALTER statements needed to close the gap and lets you review every change before executing — reducing the risk of unintended schema drift.
Write and execute Amazon Timestream queries in the integrated SQL editor with schema-aware autocomplete, syntax highlighting, and instant result display. Run scripts, inspect execution plans, and export results to CSV or JSON from a single interface.
Generate a static HTML site documenting every table, column, type, index, and relationship in your Amazon Timestream schema. Share it with your team or embed it in your project wiki — no extra tooling required.
For the full feature list and edition comparison, visit the DbSchema PRO Edition page.