WO2024125799A1

WO2024125799A1 - Method for managing a database table storage tiering and a database management system

Info

Publication number: WO2024125799A1
Application number: PCT/EP2022/086133
Authority: WO
Inventors: Eduardo Warszawski; Michael Hirsch; Assaf Natanzon
Original assignee: Huawei Technologies Co., Ltd.
Priority date: 2022-12-15
Filing date: 2022-12-15
Publication date: 2024-06-20

Abstract

Provided is a method of managing a database table storage tiering. The method includes creating a tiered storage plan for a table in a database (108) by splitting the table into shards and designating a mapping of the shards to storage tiers based on characteristics of a content of the table. The storage tiers include two or more of a high-performance storage tier, a performance storage tier, an active-archive storage tier, and an archive-storage tier. The method includes enabling a user to designate a user mapping from one or more fields of the table to one or more of the storage tiers by means of a manual input. The method includes updating the tiered storage plan based on the user mapping. The method includes storing the shards of the table on the storage tiers in accordance with the updated tiered storage plan.

Description

METHOD FOR MANAGING A DATABASE TABLE STORAGE TIERING AND A DATABASE MANAGEMENT SYSTEM

TECHNICAL FIELD

The disclosure relates generally to a database, and more particularly, the disclosure relates to a method for managing a database table storage tiering and a database management system.

BACKGROUND

A storage medium is a physical component attached to a system internally or externally that receives and retains electronic data for applications and users and enables the data available for retrieval. There are numerous storage media available in the market with different characteristics including durability, write access time, read access time, availability, granularity, cost, and the like.

Data hierarchy is introduced where it tiered on different media to exploit the storage space efficiently and to minimize costs, which optimizes the cost, and performance of the system, based on the characteristics of the storage medium and the data availability requirements. The data hierarchy may include storage tiers that include Random Access Memory, RAM, Persistent Memory, Storage Class Memory, SCM, Peripheral Component Interconnect, PCI memory, Non-Volatile Memory express, NVMe, Solid State Drive, SSD, Hard-Disk Drive, HDD, Tape, Optical, Glass and the like. The data hierarchy may be with a tiered storage model with multiple storage tiers. The storage tiers include a tier 0 including NVMe, a tier 1 including HDD, a tier 2 including HDD, and Tape, and a tier 3 including Tape, offline storage, and deep archive. These storage tiers enable ultra-high-performance of 10% in the tier 0, performance of 10% in the tier 1, active archive of 20% in the tier 2, archive with long-term of 60% in the tier 3, and air gap including offline, cloud, and vault.

Currently, the storage tiering is based on *access frequency* of the data, which matches with the cost-availability characteristics of storage layer and forecasts future use of the data based on past heuristics, where the system records time records of each datum access in the storage media, that provides forecasting the future availability requirements of the data. Artificial Intelligence, Al is also used to improve the data availability requirement predictions. Typical classes for storage tiering include mission-critical data, hot data, warm data, and cold data. The mission-critical data is a data that is *always* available quickly, where the system assigns to the fastest storage with high-reliability characteristics. The hot data is the data that is accessed most frequently, where the system assigns the fastest storage. The warm-data is data that is accessed less frequently and needs to be available upon request. The cold-data is data that is rarely or even never again accessed data which can be retained for sake of compliance or eventually to undertake big data analysis in the future. The cold data may be assigned to the most cost-effective storage layer with very long-term persistency and cost of operation of such media. Another prominent factor is the cost that determines the class of the storage to retain it. This storage tiering including discriminator criteria is based on time, and it is variable with time, which results in application of criteria on data changes with time, even if the data is immutable.

One of the greatest challenges in the storage tiering is identifying and classifying data, to match it with a most suitable storage technology layer i.e. the storage tier. Predicting which data is required and when the data is required is a difficult task, and predicting based on past behaviours also requires a lot of historic information and it is intrinsically inaccurate for dynamic scenarios, under changing conditions, or for growing organizations. Optimizing the storage utilization requires increasing the storage management complexity to unmanageable levels and raising the number of recommended tiers.

As the classification of the storage tiers varies with time, it requires complex and continuous routines of reclassification, where these procedures are complex tasks and interfere with the main tasks of the system, consuming excessive bandwidth, energy, and processing power. As the data reclassifies continuously, data movements are generated all the time, unrelated to the system activity, where increased data movements may be unsuitable for modem systems due to the data volumes, the distributed nature of the systems, and the intrinsic energy costs of the data movements. Further, over 70% of the data is cold, and any data is hot when it is created, which results in occupying a slot in the fastest tier and may take a very long time to be downgraded. The data can move to all the storage hierarchy at least once, and consume resources with each movement, where it is applicable even the data which is created once and never accessed again. Access time classification can be applied to storage objects i.e. blocks, files, and pages may lead to time data correlations that are counter-productive and generate spurious and redundant access amplification. The data which was created or accessed once at the same time not necessarily can be used together, only a portion of the data row is accessed. But the time-based classifications lead to excessive and entangled whole row data retrieval and movements and may be to data aggregations, when non-aggregable data are retrieved with the objective datum, resulting in interfering of efficient usage with upper and faster layers.

Therefore, there arises a need to address the aforementioned technical problem/drawbacks in managing a database table storage tiering with reduced data movements, and system complexity.

SUMMARY

It is an object of the disclosure to provide a method for managing a database table storage tiering and a database management system while avoiding one or more disadvantages of prior art approaches.

This object is achieved by the features of the independent claims. Further, implementation forms are apparent from the dependent claims, the description, and the figures.

The disclosure provides a method for managing a database table storage tiering and a database management system.

According to a first aspect, there is provided a method of managing a database table storage tiering. The method includes creating a tiered storage plan for a table in a database by splitting the table into shards and designating a mapping of the shards to storage tiers based on characteristics of a content of the table. The storage tiers include two or more of a high- performance storage tier, a performance storage tier, an active archive storage tier, and an archive storage tier. The method includes enabling a user to designate a user mapping from one or more fields of the table to one or more of the storage tiers by means of a manual input. The method includes updating the tiered storage plan based on the user mapping. The method includes storing the shards of the table on the storage tiers in accordance with the updated tiered storage plan. This method enables object-based object classification which results in accurate classification of the storage tiers in simplified categorization, and removes continuous reclassification processes. This method also removes time dependency in the classification of the storage tiers. This method provides storage occupancy based on retrieval patterns. This method provides better storage utilization with reduced cost and minimized data movement. This method removes unnecessary data copy operations that reduce resource and energy consumption. This method enables non-aggregable data classification which results in reduced complexity in allocation subsystem.

Optionally, the method includes updating the tiered storage plan based on an analysis of previous queries to and/or modifications of the table in the database.

Optionally, the method includes updating the tiered storage plan based on an analysis of new queries to and/or modifications of the table in the database.

Optionally, the analysis is based on a Machine Learning, ML, algorithm and/or an Artificial Intelligence, Al, algorithm. This method provides accurate initial classification based on static analysis.

Optionally, the method includes migrating shards of the table between the storage tiers if the mapping of the shards to the storage tiers is changed according to the updated tiered storage plan.

Optionally, the table is split into shards consisting of columns of the table based on a type of fields in each column.

Optionally, the table is split into shards consisting of rows based on date values comprised in a data field in each row.

Optionally, each storage tier includes one or more data storage media from a group consisting of a Random- Access Memory, RAM, a Persistent Memory, a Storage Class Memory, SCM, a Peripheral Component Interconnect, PCI, memory, a Non-Volatile Memory Express, NVMe, storage, a Solid-State Drive, SSD, a Hard Disk Drive, HDD, a magnetic tape storage, an optical storage, and a glass storage. According to a second aspect, there is provided a database management system. The database management system includes a processing unit, a user input unit, and a storage unit. The processing unit is configured for creating a tiered storage plan for a table in a database by splitting the table into shards and designating a mapping of the shards to storage tiers based on characteristics of a content of the table. The storage tiers include two or more of a high- performance storage tier, a performance storage tier, an active archive storage tier, and an archive storage tier. The user input unit is configured for enabling a user to designate a user mapping from one or more fields of the table to one or more of the storage tiers by means of a manual input. The processing unit is configured for updating the tiered storage plan based on the user mapping. The storage unit is configured for storing the shards of the table on the storage tiers in accordance with the updated tiered storage plan.

The database management system enables object-based object classification which results in accurate classification of the storage tiers in simplified categorization, and removes continuous reclassification processes. The database management system also removes time dependency in the classification of the storage tiers. The database management system provides storage occupancy based on retrieval patterns. The database management system provides better storage utilization with reduced cost and minimized data movement. The database management system removes unnecessary data copy operations that reduce resource and energy consumption. The database management system enables non-aggregable data classification which results in reduced complexity in allocation subsystem.

Optionally, the processing unit is further configured for updating the tiered storage plan based on an analysis of previous queries to and/or modifications of the table in the database.

Optionally, the processing unit is further configured for updating the tiered storage plan based on an analysis of new queries to and/or modifications of the table in the database.

Optionally, the analysis is based on a Machine Learning, ML, algorithm and/or an Artificial Intelligence, Al, algorithm. The database management system provides accurate initial classification based on static analysis. Optionally, the storage unit is configured for migrating shards of the table between the storage tiers if the mapping of the shards to the storage tiers is changed according to the updated tiered storage plan.

Optionally, each storage tier includes one or more data storage media from a group consisting of a Random- Access Memory, RAM, a Persistent Memory, a Storage Class Memory, SCM, a Peripheral Component Interconnect, PCI, memory, a Non-Volatile Memory Express, NVMe, storage, a Solid-State Drive, SSD, a Hard Disk Drive, HDD, a magnetic tape storage, an optical storage, and a glass storage.

A technical problem in the prior art is resolved, where the technical problem is managing a database table storage tiering with reduced data movements, system complexity, and accurate classification of data in the storage tiers.

Therefore, in contradistinction to the prior art, according to a method of managing a database table storage tiering and a database management system enables reduction of data movements, and system complexity, and provides better storage utilization with reduced cost, resource, and energy consumption.

These and other aspects of the disclosure will be apparent from and the implementation(s) described below.

BRIEF DESCRIPTION OF DRAWINGS

Implementations of the disclosure will now be described, by way of example only, with reference to the accompanying drawings, in which:

FIG. 1 is a block diagram of a database management system in accordance with an implementation of the disclosure; FIG. 2A is an exemplary table view in a logic view format for storing information of IDs in accordance with an implementation of the disclosure;

FIG. 2B is an exemplary table view in a tiered on-storage format in horizontal tiering for storing information of IDs in accordance with an implementation of the disclosure;

FIG. 3 A is an exemplary table view in a logic view format for storing information of IDs in accordance with an implementation of the disclosure;

FIG. 3B is an exemplary table view in a tiered on-storage format in vertical tiering for storing information of IDs in accordance with an implementation of the disclosure;

FIGS. 4A and 4B are flow diagrams that illustrate a method of managing a database table storage tiering in accordance with an implementation of the disclosure; and

FIG. 5 is an illustration of a computer system (e.g. a database management system) in which the various architectures and functionalities of the various previous implementations may be implemented.

DETAILED DESCRIPTION OF THE DRAWINGS

Implementations of the disclosure provide a method for managing a database table storage tiering and a database management system.

To make solutions of the disclosure more comprehensible for a person skilled in the art, the following implementations of the disclosure are described with reference to the accompanying drawings.

Terms such as "a first", "a second", "a third", and "a fourth" (if any) in the summary, claims, and foregoing accompanying drawings of the disclosure are used to distinguish between similar objects and are not necessarily used to describe a specific sequence or order. It should be understood that the terms so used are interchangeable under appropriate circumstances, so that the implementations of the disclosure described herein are, for example, capable of being implemented in sequences other than the sequences illustrated or described herein. Furthermore, the terms "include" and "have" and any variations thereof, are intended to cover a non-ex elusive inclusion. For example, a process, a method, a system, a product, or a device that includes a series of steps or units, is not necessarily limited to expressly listed steps or units but may include other steps or units that are not expressly listed or that are inherent to such process, method, product, or device. FIG. 1 is a block diagram of a database management system 100 in accordance with an implementation of the disclosure. The database management system 100 includes a processing unit 102, a user input unit 104, and a storage unit 106. The processing unit 102 is configured for creating a tiered storage plan for a table in a database 108 by splitting the table into shards and designating a mapping of the shards to storage tiers based on characteristics of a content of the table. The storage tiers include two or more of a high-performance storage tier, a performance storage tier, an active archive storage tier, and an archive storage tier. The user input unit 104 is configured for enabling a user to designate a user mapping from one or more fields of the table to one or more of the storage tiers by means of a manual input. The processing unit 102 is configured for updating the tiered storage plan based on the user mapping. The storage unit 106 is configured for storing the shards of the table on the storage tiers in accordance with the updated tiered storage plan.

The database management system 100 enables object-based object classification which results in accurate classification of the storage tiers in simplified categorization and removes continuous reclassification processes. The database management system 100 also removes time dependency in the classification of the storage tiers. The database management system 100 provides storage occupancy based on retrieval patterns. The database management system 100 provides better storage utilization with reduced cost and minimized data movement. The database management system 100 removes unnecessary data copy operations that reduce resource and energy consumption. The database management system 100 enables non- aggregable data classification which results in reduced complexity in allocation subsystem.

The database management system 100 creates the tiered storage plan using the processing unit 102 for splitting the table between the storage tiers, and the tiered storage plan is shown to the user. The database management system 100 enables the user to designate the mapping using the user input unit 104 to augment or modify the tiered storage plan. Optionally, the processing unit 102 is further configured for updating the tiered storage plan based on an analysis of previous queries to and/or modifications of the table in the database 108. Optionally, the processing unit 102 is further configured for updating the tiered storage plan based on an analysis of new queries to and/or modifications of the table in the database 108. Optionally, the analysis is based on a Machine Learning, ML, algorithm and/or an Artificial Intelligence, Al, algorithm. The database management system 100 provides accurate initial classification based on static analysis. The processing unit 102 may update operative changes to the tiered storage plan based on a historic analysis of query execution that determines data access patterns. Optionally, the historic analysis is based on the Machine Learning, ML, algorithm and/or the Artificial Intelligence, Al, algorithm.

Optionally, the storage unit 106 is configured for migrating shards of the table between the storage tiers if the mapping of the shards to the storage tiers is changed according to the updated tiered storage plan. For example, if an index is added or removed, the database management system 100 enables the processing unit 102 to update the tiered storage plan, and the storage unit 106 to migrate data between the storage tiers.

Optionally, the table is split into shards consisting of columns of the table based on a type of fields in each column. Optionally, the table is split into shards consisting of rows based on date values comprised in a data field in each row.

FIG. 2A is an exemplary table view 202 in a logic view format for storing information of IDs in accordance with an implementation of the disclosure. The exemplary table view 202 depicts the logic view format on the information of IDs including userID, name, address, age, and grade. The logic view format of the table may be created with:

CREATE TABLE Persons (

PersonlD int,

LastName varchar(255),

FirstName varchar(255),

Address varchar(255),

City varchar(255)

); The database management system is for different storage tiers including Non-Volatile memory, Persistent Memory, Hard-Disk Drive, HDD, Solid-State Drive, SSD, Tape, DVD, and offline storage, in a database. Rows of the database management system may be spread among the different storage tiers with a type of each column. For example, JSON column elements can be stored in slow media. But the JSON column elements may be retrieved entirely to RAM for processing. The slow media may be the offline storage. The database management system enables storing columns of IDs or userIDs in a fast tier through the horizontal tiering, where photos or XML can be stored in a slow media. Optionally, Unique values and Immutable values of data can be stored in slow media except when they are used for indexed accesses. The database management system enables storing of PersonlD (int unique) values in a fast storage tier, and FirstName and LastName (varchar) in a slow storage tier.

FIG. 2B is an exemplary table view 204 in a tiered on-storage format in horizontal tiering for storing the information of IDs in accordance with an implementation of the disclosure. The database management system enables storing of the IDs and userIDs in the Persistent memory, the names and the addresses in the HDD, and the ages and the grades in the SSD.

FIG. 3 A is an exemplary table view 302 in a logic view format for storing information of IDs in accordance with an implementation of the disclosure. The exemplary table view 302 depicts the logic view format on the information of IDs including name, and purchased. The database management system enables storing of different table shards based on the *date field* of a table for the vertical tiering. For example, a current month ledger is retained in RAM, where other months of the current year can be retained in a slow storage tier and previous year's shards can be stored in an archival storage tier, with minimal data movements. The database management system enables storing rows of upper partition range by date field in a fast storage tier, and rows of archived range by date field in a slow storage tier. The database management system may move a partition based on the *date field* when altering the exemplary table. The logic view format of the table may be altered with:

CREATE TABLE tr (id INT, name VARCHAR(50), purchased DATE) PARTITION BY RANGE( YEAR(purchased) ) (

PARTITION pO VALUES LESS THAN (1990), PARTITION pl VALUES LESS THAN (1995), PARTITION p2 VALUES LESS THAN (2000), PARTITION p3 VALUES LESS THAN (2005), PARTITION p4 VALUES LESS THAN (2010), PARTITION p5 VALUES LESS THAN (2015) );

FIG. 3B is an exemplary table view 304 in a tiered on-storage format in vertical tiering for storing the information of IDs in accordance with an implementation of the disclosure. The database management system enables storing of a first partition to Tape, a second partition to DVD, and a third partition of HDD.

FIGS. 4 A and 4B are flow diagrams that illustrate a method of managing a database table storage tiering in accordance with an implementation of the disclosure. At a step 402, a tiered storage plan for a table is created in a database by splitting the table into shards and a mapping of the shards is designated to storage tiers based on characteristics of a content of the table. The storage tiers include two or more of a high-performance storage tier, a performance storage tier, an active archive storage tier, and an archive storage tier. At a step 404, a user is enabled to designate a user mapping from one or more fields of the table to one or more of the storage tiers by means of a manual input. At a step 406, the tiered storage plan is updated based on the user mapping. At a step 408, the shards of the table are stored on the storage tiers in accordance with the updated tiered storage plan.

This method enables object-based object classification which results in accurate classification of the storage tiers in simplified categorization, and removes continuous reclassification processes. This method also removes time dependency in the classification of the storage tiers. This method provides storage occupancy based on retrieval patterns. This method provides better storage utilization with reduced cost and minimized data movement. This method removes unnecessary data copy operations that reduces resource and energy consumption. This method enables non-aggregable data classification which results in reduced complexity in allocation subsystem.

FIG. 5 is an illustration of a computer system (e.g. a database management system) in which the various architectures and functionalities of the various previous implementations may be implemented. As shown, the computer system 500 includes at least one processor 504 that is connected to a bus 502, wherein the computer system 500 may be implemented using any suitable protocol, such as PCI (Peripheral Component Interconnect), PCI-Express, AGP (Accelerated Graphics Port), Hyper Transport, or any other bus or point-to-point communication protocol (s). The computer system 500 also includes a memory 506.

Control logic (software) and data are stored in the memory 506 which may take a form of random-access memory (RAM). In the disclosure, a single semiconductor platform may refer to a sole unitary semiconductor-based integrated circuit or chip. It should be noted that the term single semiconductor platform may also refer to multi-chip modules with increased connectivity which simulate on-chip modules with increased connectivity which simulate on- chip operation, and make substantial improvements over utilizing a conventional central processing unit (CPU) and bus implementation. Of course, the various modules may also be situated separately or in various combinations of semiconductor platforms per the desires of the user.

The computer system 500 may also include a secondary storage 510. The secondary storage 510 includes, for example, a hard disk drive and a removable storage drive, representing a floppy disk drive, a magnetic tape drive, a compact disk drive, digital versatile disk (DVD) drive, recording device, universal serial bus (USB) flash memory. The removable storage drive at least one of reads from and writes to a removable storage unit in a well-known manner.

Computer programs, or computer control logic algorithms, may be stored in at least one of the memory 506 and the secondary storage 510. Such computer programs, when executed, enable the computer system 500 to perform various functions as described in the foregoing. The memory 506, the secondary storage 510, and any other storage are possible examples of computer-readable media.

In an implementation, the architectures and functionalities depicted in the various previous figures may be implemented in the context of the processor 504, a graphics processor coupled to a communication interface 512, an integrated circuit (not shown) that is capable of at least a portion of the capabilities of both the processor 504 and a graphics processor, a chipset (namely, a group of integrated circuits designed to work and sold as a unit for performing related functions, and so forth).

Furthermore, the architectures and functionalities depicted in the various previous-described figures may be implemented in a context of a general computer system, a circuit board system, a game console system dedicated for entertainment purposes, an application-specific system. For example, the computer system 500 may take the form of a desktop computer, a laptop computer, a server, a workstation, a game console, an embedded system.

Furthermore, the computer system 500 may take the form of various other devices including, but not limited to a personal digital assistant (PDA) device, a mobile phone device, a smart phone, a television, and so forth. Additionally, although not shown, the computer system 500 may be coupled to a network (for example, a telecommunications network, a local area network (LAN), a wireless network, a wide area network (WAN) such as the Internet, a peer-to-peer network, a cable network, or the like) for communication purposes through an I/O interface 508.

It should be understood that the arrangement of components illustrated in the figures described are exemplary and that other arrangement may be possible. It should also be understood that the various system components (and means) defined by the claims, described below, and illustrated in the various block diagrams represent components in some systems configured according to the subject matter disclosed herein. For example, one or more of these system components (and means) may be realized, in whole or in part, by at least some of the components illustrated in the arrangements illustrated in the described figures.

In addition, while at least one of these components are implemented at least partially as an electronic hardware component, and therefore constitutes a machine, the other components may be implemented in software that when included in an execution environment constitutes a machine, hardware, or a combination of software and hardware.

Although the disclosure and its advantages have been described in detail, it should be understood that various changes, substitutions, and alterations can be made herein without departing from the spirit and scope of the disclosure as defined by the appended claims.

Claims

1. A method of managing a database table storage tiering, comprising: creating a tiered storage plan for a table in a database by splitting the table into shards and designating a mapping of the shards to storage tiers based on characteristics of a content of the table, the storage tiers comprising two or more of a high-performance storage tier, a performance storage tier, an active archive storage tier, and an archive storage tier, enabling a user to designate a user mapping from one or more fields of the table to one or more of the storage tiers by means of a manual input, updating the tiered storage plan based on the user mapping, and storing the shards of the table on the storage tiers in accordance with the updated tiered storage plan.

2. The method of claim 1, further comprising: updating the tiered storage plan based on an analysis of previous queries to and/or modifications of the table in the database.

3. The method of claim 1 or 2, further comprising: updating the tiered storage plan based on an analysis of new queries to and/or modifications of the table in the database.

4. The method of claim 2 or 3, wherein the analysis is based on a Machine Learning, ML, algorithm and/or an Artificial Intelligence, Al, algorithm.

5. The method of any of claims 1 to 4, further comprising: migrating shards of the table between the storage tiers if the mapping of the shards to the storage tiers is changed according to the updated tiered storage plan.

6. The method of any of claims 1 to 5, wherein the table is split into shards consisting of columns of the table based on a type of fields in each column.

7. The method of any of claims 1 to 5, wherein the table is split into shards consisting of rows based on date values comprised in a data field in each row.

8. The method of any of claims 1 to 7, wherein each storage tier comprises one or more data storage media from a group consisting of a Random-Access Memory, RAM, a Persistent Memory, a Storage Class Memory, SCM, a Peripheral Component Interconnect, PCI, memory, a Non-Volatile Memory Express, NVMe, storage, a Solid-State Drive, SSD, a Hard Disk Drive, HDD, a magnetic tape storage, an optical storage, and a glass storage.

9. A database management system (100), comprising: a processing unit (102) configured for creating a tiered storage plan for a table in a database (108) by splitting the table into shards and designating a mapping of the shards to storage tiers based on characteristics of a content of the table, the storage tiers comprising two or more of a high-performance storage tier, a performance storage tier, an active archive storage tier, and an archive storage tier, a user input unit (104) configured for enabling a user to designate a user mapping from one or more fields of the table to one or more of the storage tiers by means of a manual input, wherein the processing unit (102) is configured for updating the tiered storage plan based on the user mapping, and a storage unit (106) configured for storing the shards of the table on the storage tiers in accordance with the updated tiered storage plan.

10. The database management system (100) of claim 9, wherein the processing unit (102) is further configured for updating the tiered storage plan based on an analysis of previous queries to and/or modifications of the table in the database (108).

11. The database management system (100) of claim 9 or 10, wherein the processing unit (102) is further configured for updating the tiered storage plan based on an analysis of new queries to and/or modifications of the table in the database (108).

12. The database management system (100) of claim 10 or 11, wherein the analysis is based on a Machine Learning, ML, algorithm and/or an Artificial Intelligence, Al, algorithm.

13. The database management system (100) of any of claims 9 to 12, wherein the storage unit (106) is configured for migrating shards of the table between the storage tiers if the mapping of the shards to the storage tiers is changed according to the updated tiered storage plan.

14. The database management system (100) of any of claims 9 to 13, wherein the table is split into shards consisting of columns of the table based on a type of fields in each column.

15. The database management system (100) of any of claims 9 to 13, wherein the table is split into shards consisting of rows based on date values comprised in a data field in each row.

16. The database management system (100) of any of claims 9 to 15, wherein each storage tier comprises one or more data storage media from a group consisting of a Random-Access Memory, RAM, a Persistent Memory, a Storage Class Memory, SCM, a Peripheral Component

Interconnect, PCI, memory, a Non-Volatile Memory Express, NVMe, storage, a Solid-State Drive, SSD, a Hard Disk Drive, HDD, a magnetic tape storage, an optical storage, and a glass storage.