30th March 2024
This page covers recent e6data updates, including catalog privileges for column masking and row filtering, query history enhancements, and support for deletion vectors in Iceberg tables.
Last updated
This page covers recent e6data updates, including catalog privileges for column masking and row filtering, query history enhancements, and support for deletion vectors in Iceberg tables.
Last updated
We're excited to announce the latest updates and enhancements to e6data. This release brings a host of new features, improvements, and bug fixes to enhance your experience with our platform.
We're excited to announce the latest enhancements to our platform! In this release, we've introduced powerful new features: column masking and row filtering privileges. These capabilities empower administrators to control access to sensitive data within their databases finely, ensuring enhanced data security and compliance.
Column masking privilege allows administrators to control the visibility of specific column data within a database table. It enables the hiding of sensitive information based on predefined rules, ensuring data security and privacy. Authorised users can apply masking techniques like redaction, partial display, or hashing to protect confidential data. For more information, please refer to the .
Row filtering privilege enables users to control access to specific rows of data within a database table. It allows administrators to define conditions based on SQL expressions, restricting the visibility of sensitive or confidential information. Authorised users can create row filters to limit access to data based on criteria such as user roles, departments, or other relevant factors, ensuring data security and compliance with privacy regulations. For more information, please refer to the .
We're excited to announce the launch of our latest API feature: the Query History Query Count API.
We're thrilled to announce that the SQL engine now supports reading deletion vectors for enhanced storage optimization in Iceberg tables.
Deletion vectors enable DELETE operations to mark existing rows as removed without rewriting the entire Parquet file, thereby improving performance and efficiency.
Applying filters on columns from which data has been deleted in complex data types is not currently supported.
This enhancement brings significant benefits to your data management processes, offering improved performance and storage efficiency.
We're excited to introduce a variety of new functions to enhance your querying capabilities:
STRPOS: This function enables you to find the position of a substring within a string. It returns the position of the first occurrence of the substring within the string. If the substring is not found, it returns zero.
LENGTH: The LENGTH function allows you to determine the length of a string.
STARTSWITH: The STARTSWITH function simplifies substring search operations by returning TRUE if the first expression starts with the second expression.
These new functions provide additional flexibility and efficiency to your data manipulation tasks.
This powerful tool allows users to retrieve the count of queries executed within a specified time range, filtered based on selections made in the query history. With this API, users can now effortlessly track query activity, analyze usage trends, and gain valuable insights into their data analytics workflows. Whether you're monitoring system performance or optimizing query efficiency, the Query History Query Count API provides a streamlined solution for accessing vital query execution metrics. For more information, please refer to the .