General Availability of GridDB 5.3 Enterprise Edition

~ Major Enhancement in IoT and Time Series Data Analysis Functionalities ~

May 16, 2023
Toshiba Digital Solutions Corporation

KAWASAKI―Toshiba Digital Solutions Corporation (Toshiba) today announced the general availability of GridDB 5.3 Enterprise Edition (GridDB 5.3 EE), a purpose-built database for IoT and Big Data workloads. The latest version features improvements in IoT and time series data analysis functionalities.

Recently, time series data analysis has gained prominence as IoT use cases diversify and expand to different industries. Built-in time series data functions that accommodate different characteristics of IoT data such as data interpolation to fill in missing values due to sensor failure or communication error, grouping time series data into specific time intervals and applying data aggregation for analysis, as well as the ability to collect time series data at higher granularity for a more comprehensive and accurate data analysis are in great demand.

In response to these needs, GridDB 5.3 EE is now equipped with improved time series data aggregation function, automatic data interpolation to fill in missing data, and the ability to collect time series data with nanosecond precision (one billionth of a second) to facilitate and simplify IoT data analysis. 

Major improvement in GridDB 5.3 EE

1. Time Series Data Aggregation
Time series data can now be grouped into time intervals and combined with aggregation functions to extract the maximum, minimum, average, and total values of these intervals. This function has been incorporated directly into GridDB to facilitate and speed up time series data analysis as it eliminates the need to extract and aggregate data on the application side.

In addition, data collection frequency has increased, resulting in massive data storage that is costly to maintain. Using this function, data for long-term storage can be thinned out (downsampling) to significantly reduce the volume of data to be stored.

2. Interpolation of Missing Values
When collecting IoT data, sensor failure or error during data transmission can occur and lead to loss of data. Missing values can cause problems and result in inaccurate analysis and predictions by AI. Therefore, in GridDB 5.3 EE, a function that automatically interpolates and fills in missing values using linear interpolation has been developed. This allows for data continuity and enables highly accurate analysis and forecasting.

3. Nanosecond (billionth of a second) Data Processing
As data collection methods and the performance of measuring instruments have greatly improved in the last few years, collecting high-granularity data such as stock prices, medical equipment data, and network monitoring data is becoming essential. In the previous version of GridDB, data can be stored up to millisecond (1/1000th of a second) accuracy. From GridDB 5.3 EE onwards, data can now be stored at higher granularity at nanosecond accuracy. This allows data to be collected and analyzed at one million times higher resolution than that of the conventional system, enabling more accurate analysis and forecasting.

4. Audit Log Enhancement
In recent years, many incidents surrounding information leaks and falsification due to identity theft have occurred. Strengthening database security is now considered one of the top priorities by many companies. Database audit is seen as an important method to encounter security threats such as database "unauthorized access" and "unauthorized operation". In GridDB 5.3 EE, audit logs such as access logs, operation logs, and error logs can be recorded and stored comprehensively for a longer period as compared to the previous versions. This makes it possible to track who did what, when, and how.

Future development of GridDB and GridDB Cloud will continue towards the support for digital transformation and cyber physical system using IoT and Big Data.

About GridDB
Toshiba developed GridDB entirely in-house, drawing on its extensive expertise in diverse industry verticals. GridDB ensures efficient accumulation of massive volumes of time series data, and to deliver scale-out performance. It features time series data management, petabyte-scale performance, excellent scalability and unwavering reliability, and developer-friendly API—essential characteristics of IoT and Big Data database.

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