Working with timestamp formats in Redshift and Athena

When working with big data and analytical platforms like Amazon Redshift and AWS Athena, managing date and time data effectively is crucial. Timestamp formats are widely used for tracking events, analyzing trends, and generating reports. However, each platform handles timestamps slightly differently, making it essential for developers and data analysts to understand how to parse, format, and manipulate timestamp values properly.

In this blog, we’ll explore how timestamps work in Amazon Redshift and AWS Athena, how to convert between formats, and best practices for querying and using time-based data.


Understanding Timestamps

A timestamp represents a point in time, typically including both the date and the time (e.g., 2025-05-24 14:30:00). It is often stored in UTC format, though it can be converted to local time zones for specific use cases.

Common timestamp formats:

  • 'YYYY-MM-DD HH:MI:SS'
  • 'YYYY-MM-DDTHH:MI:SSZ' (ISO 8601 format)
  • Unix epoch time (INT values representing seconds since Jan 1, 1970)


Timestamps in Amazon Redshift

Redshift supports two main timestamp types:

  • TIMESTAMP: without time zone information
  • TIMESTAMPTZ: with time zone support


Inserting Timestamps

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INSERT INTO events (event_time) VALUES ('2025-05-24 12:00:00');

Formatting and Parsing

You can convert between strings and timestamps using TO_TIMESTAMP():


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SELECT TO_TIMESTAMP('2025-05-24 12:30:00', 'YYYY-MM-DD HH24:MI:SS');

You can also extract parts of the timestamp:


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SELECT EXTRACT(YEAR FROM event_time), EXTRACT(MONTH FROM event_time) FROM events;

To format timestamps into strings:


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SELECT TO_CHAR(event_time, 'YYYY-MM-DD HH24:MI:SS') FROM events;

Working with Time Zones

Use CONVERT_TIMEZONE() to shift between time zones:


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SELECT CONVERT_TIMEZONE('UTC', 'America/New_York', event_time) FROM events;

Timestamps in AWS Athena

Athena uses Presto SQL under the hood, which supports rich timestamp functions.


Athena recognizes multiple timestamp formats automatically, especially ISO 8601. You can cast and parse strings using CAST and date_parse.


Casting Strings to Timestamps

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SELECT CAST('2025-05-24 14:45:00' AS timestamp);

Or use date_parse for custom formats:


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SELECT date_parse('24-05-2025 14:45', '%d-%m-%Y %H:%i');

Formatting Timestamps

Use date_format() to format timestamps into strings:


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SELECT date_format(current_timestamp, '%Y-%m-%d %H:%i:%s');

Extracting Components

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SELECT year(event_time), month(event_time), day(event_time) FROM events;

Handling Time Zones

Athena uses UTC by default. If you need to display a local time:


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SELECT at_timezone(current_timestamp, 'Asia/Kolkata');

Best Practices

  • Use ISO 8601 Format: Always store and transmit timestamps in standard formats to avoid parsing issues.
  • Store in UTC: Keep timestamps in UTC and convert to local times at the application level if necessary.
  • Avoid String Comparisons: Use native timestamp types for filtering and comparisons.
  • Use Explicit Format Strings: When parsing strings to timestamps, always specify the format to avoid ambiguity.


Conclusion

Handling timestamps effectively in Amazon Redshift and AWS Athena is vital for accurate data analysis and reporting. While both platforms offer powerful timestamp functions, being consistent with formats and understanding how to manipulate date-time values can save a lot of debugging and improve query performance. By following the best practices and leveraging built-in functions, you can make your time-based data work seamlessly across your AWS analytics stack.


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