WO2016009239A1 - Method and system for database selection - Google Patents
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- WO2016009239A1 WO2016009239A1 PCT/IB2014/001331 IB2014001331W WO2016009239A1 WO 2016009239 A1 WO2016009239 A1 WO 2016009239A1 IB 2014001331 W IB2014001331 W IB 2014001331W WO 2016009239 A1 WO2016009239 A1 WO 2016009239A1
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
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Abstract
A method and database selection system for selecting at least one database from a plurality of databases is disclosed. The method comprises a step of filtering out a first set of databases from the plurality of databases based on at least one requirement from the one or more requirements and a step of evaluating one or more weights for a second set of databases from the plurality of databases wherein at least one weight of the one or more weights is assigned to one or more databases of the second set of databases. At next step of the method disclosed in the present invention the at least one database of the second set of databases are ranked on the basis of the one or more weights and the one or more requirements.
Description
TITLE : METHOD AND SYSTEM FOR DATABASE SELECTION
Description
The present invention relates to a method and system for selecting databases and more particularly, to a method and system for automatic selection of database for any specific user requirements from a plurality of available databases.
Database is a collection of data that is related to a particular topic or purpose. Over the past years, use of database for storing and retrieving data has emerged as an important tool in a wide variety of commercial applications. Initially, many database systems operated on a single server installation with multiple users. However, various factors have developed over the . years that have required the basic nature of database architecture to change. The factors are like requirement of large database storage, large number of users accessing the databases and so on.
In present times, lot of organizations are struggling with data management issues due to the large volume of data, different forms of data, different types of data handling systems and the different kinds of processing that are required for different clients. In the last few years, there has been a dramatic growth in the number of new databases that attempt to address the above mentioned issues with respect to data management. The new databases are classified under various categories like bibliographic databases, graph databases, document-oriented databases, online databases, real-time databases and so on. The databases are classified on the basis of internal architecture, storage type and data retrieval capabilities.
Due to the availability of various databases of different types, the organizations using traditional relational database management system have an opportunity to shift to a new database which is more suitable and in line of the
processes and structures of the organizations. But due to the availability of large number of databases with different kind of capabilities and support functions this becomes a challenge for an organization or a working group to identify an appropriate database from the available databases which support the organizational existing information technology infrastructure and process. In addition to this, the selected database should also be capable of storing and processing the data in accordance with the organizational requirements.
It is clear from the foregoing if an organization chooses an inappropriate database, the functionality of the organization and the products are likely to perform in an inefficient manner which in turn will negatively affect the growth of the organization.
It is clearly evident from the above description, that the selection of an appropriate database is a very important factor for any organization. There are lot of factors that should be considered at the time of selecting a database along with the requirements. Mostly, an appropriate database is identified through a manual process. The organizations hire experts and architects to evaluate various databases on the basis of requirements and suggest few most appropriate databases. In manual process, a team of experts and architects create an evaluation matrix of the most stable data stores available in the market with the specific requirements of the organization. The databases are ranked manually based on competency with respect to addressing a particular requirement of the organization. Then a database that suits to the requirements of the organization is selected on the basis of frequency distribution of the ranks of the databases. The manual process is tedious as most of the open source distributed data stores are evolving over time, with additional features added in every release of the databases to improve the performance, reliability and user experience of the technology. Also, the requirements of the organization may change over time requiring a re-evaluation
of the upgraded databases with the new requirements of the organization .
Due to the reasons mentioned above, it is clear that the manual process of selecting a data base is expensive and time consuming. In addition to this, there is no system or method known in the state of the art that can automate database selection process to speed up the decision-making process and reduce overall cost. Hence there is a strong need of a fast and cheap, method and system for selecting a database from the available databases, with less manual intervention.
It is therefore an object of the present invention to provide an automated method and a system for selecting a database based on the user requirements.
The object is achieved by providing a method for selecting at least one database from a plurality of databases based on one or more requirements according to claim 1, and a database selection system for selecting at least one database from a plurality of databases according to claim 10. Further embodiments of the present ίηνβη^οη are addressed in the dependent claims .
In a first aspect of the present invention, a method for selecting at least one database from a plurality of databases based on one or more requirements is disclosed. The method comprises a step of filtering out a first set of databases from the plurality of databases based on at . least one requirement from the one or more requirements and a step of evaluating one or more weights for a second set of databases from the plurality of databases wherein at least one weight of the one or more weights is assigned to one or more databases of the second set of databases. At next step of the method disclosed in the present invention the at least one database of the second set of databases are ranked on the basis of the one or more weights and the one or more requirements .
In accordance with the first aspect of the present invention, the. method further comprises a step of receiving the one or more requirements from at least one user through at least one input editor before filtering out the first set of databases. The one or more requirements received from the at least one user includes the one or more weights corresponding to the one or more requirements .
Further, in accordance with the first aspect of the present invention, the method further comprises a step of receiving one or more answers for one or more requirement questions from the at least one user before filtering out the first set of databases. The one or more answers received from the at least one user include the one or more requirements. The one or more answers of the one or more requirement questions also include the one or more weights.
Furthermore in accordance with the first aspect of the present invention, the method step for evaluating the one or more weights for the second set of databases further comprises a step of comparing the one or more requirements with databases benchmarking data stored in at least one knowledge base .
In addition to it, according to the first aspect of the present invention, the method further comprises a step of displaying one or more parameters of the at least one database to one or more users after ranking the at least one database of the second set of databases. The one or more parameters of the at least one database include a rank associated with each database of the at least one database.
In a second aspect of the present invention, ■ a database selection system for selecting at least one database from a plurality of databases is disclosed. The database selection system disclosed as the second aspect of the present invention comprises at least' one input editor for receiving '
one or more requirements from at least one user, at least one data analyzer for ranking the at least one database of the plurality of databases based on the one or more requirements, at least one knowledge store for storing benchmarking data of the plurality of databases and at least one project store for storing the one or more requirements and ranks of the at least one database. The at least one project store also stores a historical data in form of user defined projects. The historical data includes one or more user past requirements and one or more lists of ranked databases corresponding to the one or more user past requirements.
In accordance to the second aspect of the present invention, the at least one input editor of the database selection system further comprises at least one user interface for receiving the one or more requirements from at least one user. The one or more requirements received from the user include one or more weights.
Further, in accordance with the second aspect of the present invention, the at least one input editor of the database selection system further comprises at least one display for displaying one or more parameters of the at least one database. The one or more parameters include a rank for each database of the at least one database.
Accordingly, the present invention provides a method and a database selection system for selecting at least one database from a plurality of databases.
The present invention is further described hereinafter with reference to illustrated embodiments shown in the accompanying drawings, in which:
FIG 1 illustrates a schematic view of a database selection system in accordance with an embodiment of the present invention,
FIG 2 illustrates · an exemplary requirement questionnaire in accordance with an embodiment of the present invention,
FIG 3 illustrates exemplary database information in accordance with an embodiment of the present invention, and
FIG 4 illustrates method steps for ranking a plurality of databases in accordance with an embodiment of the present invention.
Various embodiments are described with reference to the drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for purpose of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more embodiments. It may be evident that such embodiments may be practiced without these specific details.
Referring to FIG 1, a schematic view of a database selection system 100 is illustrated.
The database selection system 100 includes an input editor 102, a database analyzer 104, a knowledge store 106 and a project store 108. The input editor 102 is a graphical user interface (GUI) based editor that allows a user to' view, create, modify and delete requirements related to the selection of a database from the plurality of databases stored in the knowledge store 106. The input editor 102 receives various inputs from the user through a connection 110, as shown in FIG 1. The input editor 102 provides suitable controls and features that allow the user to create and store a new database selection project in the project store 108 along with entering the database requirements in accordance with one or more questions prompted by the user interface of the input editor 102. An exemplary set of the one or more questions, in accordance with an embodiment of
the present invention, are illustrated in FIG 2. In another embodiment of the present invention, the user interface of the input editor provides a mechanism to assign weights to at least one of the one or more questions in order to elicit one or more high priority requirements of selecting the database. The input editor 102 also facilitates the user to open, view, modify and delete one or more database selection projects that are stored in the project store 108.
In addition to this, the input editor is also capable of sending analysis instructions to the database analyzer 104 and receiving a set of results based on the analysis from the database analyzer 104. The set of results may include one or more ranked databases from a list of a plurality of databases stored in the knowledge store 106 and the one or more ranked databases are in accordance with one or more answers of the one or more questions inputted by the user at the user interface of the input editor 102. In a preferred embodiment, of the present invention, the user interface of the input editor 102 displays the one or more, ranked databases along with one or more guiding options for the user. The one or more guiding options may include one or more tuning parameters for configuring and/or optimizing the one or more suitable databases. In the preferred embodiment the user interface of the input editor 102 also provides one or more suggestions to the user to modify a list of the one or more ranked databases on the basis of user requirements. Further, the user interface of the input editor 102 facilitates the user to selectively accept and/or selectively reject the one or more suggestions provided by the user interface. Furthermore, the user interface of the input editor 102 provides one or more generic options to the user. The one or more generic options include storing the list of the one or more ranked databases and/or exporting the list of the one or more ranked databases to one or more files or one or more pre-existing databases in one or more formats. The one or more formats include, but not limited to, .txt, .xml, .html and so on.
The database analyzer 104 receives user requirements as the one or more answers of the one or more questions from the input editor 102 as shown in FIG 1. The database analyzer 104 communicates with the knowledge base 106 and identifies the list of one or more databases based on the user requirements received from the input editor 102 and databases benchmarking data stored in the knowledge base 106. The database analyzer 104 provides rankings to the one or more identified databases and sends the list of the one or more ranked databases identified from the · knowledge base 106, based on the user requirements and the databases benchmarking data, to the input editor 102 along with the rankings. A method of identifying and ranking the one or more databases is described with the help of an example in following figures.
In an embodiment of the present invention, the database analyzer 104 also analyzes additional configuration options for each of the user requirements and identifies one or more additional databases from the knowledge base 106. The databases analyzer 104 ranks the one or more additional databases along with the one or more identified databases and sends the one or more additional databases to the input editor 102 along with the list of one or more ranked databases identified in accordance with the user requirements .
The knowledge base 106 is a storing unit which stores information about available and/or known databases. The knowledge base 106 also stores the database benchmarking data along with a comprehensive list of one or more configuration and/or one or more tuning parameters for each database known in the stare of the art. The one or more configuration and/or the one or more tuning parameters for each database are accompanied by a set of values for each parameter and each value of the configuration and/or tuning parameters corresponds to . a particular behaviour of a corresponding database. The knowledge base 106 is being created and made
available to the database analyzer 104 by using scientific and automated methods known in the state of the art. The knowledge base 106 stores the data in a database, or in a file or any format known in the state of the art. In another embodiment of the present invention, the knowledge base 106 is capable of storing data in one or more memory units associated with a local system or a remote system or in cloud.
The project store 108 stores a plurality of database selection projects created by one or more users. Each database selection project of the plurality of database selection projects includes database requirements entered by one or more users along with optional weights assigned to each database requirement. A database selection project also includes a historical data related to the database selection project. The historical data includes all the changes and/or modifications, done by the one or more users, in the database requirements and also in the optional weights assigned to the database requirements. Each database selection project also includes the list of the one or more ranked databases identified by the database analyzer 104 after analyzing the requirements entered by the one or more users. Further each database selection project also includes the one or more configuration and/or the one or more tuning parameters selected by the one or more users for the one or more database identified by the database analyzer .104. The historical data of the project store 108 also includes the lists of the one or more ranked databases identified by the database analyzer along with the configuration and tuning parameters selected by the one or more users in past.
Referring now to FIG 2, an exemplary requirement questionnaire 200 is illustrated in accordance with an embodiment of the present invention. The exemplary requirement questionnaire 200 is an exemplary set of questions that are displayed on the user interface of the input editor 102 as illustrated in FIG 1. The user provides
the requirement for the database by answering the questions of the requirement questionnaire 200. The requirement questionnaire 200 also has an answer column, where the user can provide answers for each question of the requirement questionnaire 200. In another embodiment of the present invention the user can answer the one or more questions of the requirement questionnaire 200 by using one or more answering techniques. The one or more answering techniques include, but not limited to, text box, drop down menu, radio button, selection range and so on. In addition to this, the requirement questionnaire 200 includes a weight column, where user can provide an indicative instruction related to the importance of a parameter asked in a question of the requirement questionnaire 200.
In an exemplary embodiment of the present invention, assuming the user is planning to use Microsoft Windows as operating system, so the answer of Ql of the exemplary requirement questionnaire 200 will be Microsoft Windows. Assuming the use of Microsoft Windows as operating system- is very important for the user, so the user can slide a marker 202 towards a wider side of a slider 204. The marker 202 at the wider side of the slider 204 indicates that Microsoft Windows as operating system is an extremely important parameter for the user and the user is only interested in the databases which can support Microsoft Windows as operating system. In an embodiment of the present invention, the weight column is an optional column and the user only indicates the importance of the parameter asked in the question if required.
The method, described in FIG 2, is for indicating the importance of the parameters asked in a question of the requirement questionnaire 200 is for demonstration purpose. In other embodiments of the present invention other indication methods, known in the state of the art, can be used for indicating the. importance of the parameters.
In another embodiment of the present invention, the questions of the exemplary requirement questionnaire 200 can be categorized under one or more categories. The one or more categories include, but not limited to, basic requirements, throughput requirements, query expressiveness, nice-to-have features and so on.
Referring now to FIG 3, exemplary database information 300 stored in the knowledge base 106 of FIG 1 is shown in accordance with an embodiment of the present invention. The exemplary database information 300 is stored in a tabular format as shown in FIG 3. In other embodiments of the present invention the database information can be stored in any format known in the state of the art.
The exemplary database information 300 includes information of four databases namely, Couch DB, Mongo DB, Cassandra and MS SQL. In an embodiment of the present invention, the exemplary database information 300 may include information of one or all databases, known in the state of the art. The exemplary database information 300 shown in FIG .3 also includes a plurality of evaluation criteria for all the databases mentioned in the exemplary database information 300. Each evaluation criteria of the plurality of evaluation criteria is related to the one or more questions of the requirement questionnaire 200, as shown in FIG 2. The database analyzer 104 of FIG 1, compares the plurality of evaluation criteria for each database information available in the knowledge base 106 with the one or more answers received from the user for each question of the requirement questionnaire 200 to identify the list of the one or more ranked databases that are most suitable in accordance with the user requirements . The method of ranking the plurality of databases available in the knowledge base 106 by using the one or more answers of the one or more questions of the requirement questionnaire 200 is explained in a subsequent figure.
Referring to FIG 4, a flow chart of the method steps for ranking the plurality of databases, by the database analyzer 104, is shown in accordance with an embodiment of the present invention. The database analyzer 104, of FIG 1, ranks the plurality of databases on the basis of the database information 300 of FIG 3 stored in the knowledge base 106 of FIG 1 and the one or more answers provided and weights assigned by the user for the one or more questions of the requirement questionnaire 200 of FIG 2.
At step 402, the database analyzer 104 filter outs some of the databases based on one or more basic requirements mentioned by the user as the one or more answers of the requirement questionnaire 200. The one or more basic requirements may include type of operating system as asked under first question i.e. Ql of the exemplary requirement questionnaire 200 as shown in FIG 2. The questions from Q2 to Q4 of the exemplary requirement questionnaire 200, as shown in FIG 2, can also be a part of the basic requirements. The one or more questions mentioned under the basic requirements in accordance with the exemplary requirement . questionnaire 200 are for illustration purposes. In another embodiment of the present invention the basic requirements may include any question related to the user requirements. In an exemplary embodiment of the present invention if the user' s answer for the question Ql, of the exemplary requirement questionnaire 200 of FIG 2, is Linux then the data analyzer 104 will filter out MS-SQL from the list of the exemplary database information 300 illustrated in FIG 3. In other words, if the user enters Linux as an answer of the question Ql of requirement questionnaire 200, then from the list of available databases, shown in FIG 3, it is clear that MS-SQL is not suitable database for a system having Linux operating system hence,, at the step 402 of the disclosed method, the database analyzer 104 will rule out MS-SQL for the list of the one or more databases which can be suitable for the user. The preferred and alternate methods for filtering out of the one or more databases are explained in preceding figures.
At step 404 of the method for ranking the one or more databases, the database analyzer 104 computes a score for each remaining database, after the step 402, in the list of databases available in the knowledge base 106. The scores are computed on the basis of the weights specified by the user for the one or more questions of the exemplary requirement questionnaire 200, as illustrated in FIG 2. In an exemplary embodiment of the present invention, assuming the weights assigned by the user to all the questions of the exemplary requirement questionnaire 200 has numeric value 1 and the answer for Ql, of the exemplary requirement questionnaire 200, is Linux. From the answer of Ql, from the list of databases illustrated in FIG 3, MS-SQL is filtered out, as explained in the method step 402. Now based on the exemplary weights assigned to the one or more questions, of the requirement questionnaire 200, by the user i.e. numeric value 1, the scores of the remaining databases i.e. Couch DB, Mongo DB and Cassandra, from the four databases mentioned in the exemplary database information 300 of FIG 3, will be determined by the database analyzer 104. The database analyzer 104, of FIG 1, evaluates the rank of the remaining databases from the scores determined with the help -of weight assigned by the user to the one or more questions of the requirement questionnaire 200, as illustrated in FIG 2. For example, assuming the user's answer for Q12 of the requirement questionnaire 200 is "Yes" i.e. the user need support for aggregated queries and from the database information 300, of FIG 3, it is clear that the aggregated queries are supported by Mongo DB and not by Couch DB and Cassandra, so the score for Q12 will be "1" for Mongo DB and "0" for Couch DB and Cassandra. In the example, the score for MS-SQL will not considered as it is already filtered out by the database analyzer 104 at the previous step i.e. step 402 of the ranking method.
Based on the scores computed by the database analyzer, as explained in the above example, a database from the remaining
databases which get maximum score will be ranked as a top most database i.e. most suitable database for the user requirements. The most suitable database i.e. the database with maximum score will be followed by the other databases from the remaining databases in a chronological order based on the scores evaluated by the database analyzer 104. In a preferred embodiment, the database analyzer 104 also provides one or more suggestions to the user based on the one or more configuration or the one or more tuning parameters of the remaining databases as explained in preceding figures. In another embodiment of the present invention, the scores can also be computed by the database analyzer based on the one or more categories of the questions of the requirement questionnaire 200, as explained in FIG 2.
At the last step of the method i.e. at step 406, the list of the one or more raked databases from the remaining databases will be presented to the user through the user interface of the input editor 102, as illustrated in FIG 1. The list may also include one or more recommended databases. The one or more recommended databases are from the remaining databases which the database analyzer 104 finds suitable in accordance to the one or more weights provided by the user, as explained above. In addition to it, the user also receives one or more options to accept or reject the one or more recommended databases and/or to modify, add, delete the requirements along with the list of the one or more ranked databases at the user interface of the input editor 102, as described in FIG 1. The preferred and alternate methods for displaying of the list of the one or more ranked databases are explained in the preceding figures.
It is evident from the foregoing description of the present invention that the invention discloses an automated method and a system for selecting a database based on the user requirements .
The present invention also discloses a method and a system for ranking a plurality of databases based on the scores of the plurality of databases evaluated from in accordance with the requirements of the user.
In addition to this, the invention also discloses a method and a system for ranking the plurality of databases based on the scores evaluated by using the weights assigned by the user to each of the database requirements.
The method and system disclosed in the present invention provides an efficient, cost effective, user friendly and automated technique for identifying a database from the plurality of available databases that is most appropriate and suitable in light of the user requirements received as input.
While the present invention has been described in detail with reference to certain embodiments, it should be appreciated that the present invention is not limited to those embodiments. In view of the present disclosure, many modifications and variations would present themselves, to those, of skill in the art without departing from the scope of various embodiments of the present invention, as described herein. The scope of the present invention is, therefore, indicated by the following claims rather than by the foregoing description. All changes, modifications, and variations coming within the meaning and range of equivalency of the claims are to be considered within their scope.
Claims
aims :
A method for selecting at least one database from a plurality of databases based on one or more requirements, the method comprising:
-filtering out a first set of databases from the plurality of databases based on at least one requirement from the one or more requirements;
-evaluating one or more weights - for a second set of databases from the plurality of databases wherein at least one weight of the one or more weights is assigned to one or more databases of the second set of databases; and
-ranking the at least one database of the second set of databases on the basis of the one or more weights and the one or more requirements.
The method according to claim 1 further comprises a step of receiving the one or more requirements from at least one user through at least one' input editor (102) before filtering out the first set of databases.
The method according to claim 2 wherein the one or more requirements include the one or more weights.
The method according to claim 1 further' comprises a step of receiving one or more answers for . one or more requirement questions from the at least one user before filtering out the first set of databases .
The method according to claim 4 wherein the one or more answers include the one or more requirements.
The method according to claim 4 wherein the one or more answers include the one or more weights .
The method according to claim wherein evaluating the one or more weights for the econd set of databases
further comprises a step of comparing the one or more requirements with databases benchmarking data.
8. The method according to claim 1 further comprises a step of displaying one or more parameters of the at least one database to one or more users after ranking the at least one database of the second set of databases. 9. The method according to claim 8 the one or more parameters include a rank associated with each database of the at least one database.
10. A database selection system (100) for selecting at least one database from a plurality of databases, the database selection system (100) comprises:
-at least one input editor (102) for receiving one or more requirements;
-at least one data analyzer (104) for ranking the at least one database of the plurality of databases based on the one or more requirements;
-at least one knowledge store (106) for storing benchmarking data of the plurality of databases; and -at least one project store (108) for storing the one or more requirements and ranks of the at least one database .
11. The system according to claim 10 wherein the at least one input editor (102) further comprises at least one user interface for receiving the one or more requirements from at least one user.
12. The system according to claim 10 wherein the at least one input editor (102) further comprises at least one display for displaying one or more parameters of the at least one database wherein the one or more parameters include a rank for each database of the at least one database.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| EP14762091.8A EP3170098A1 (en) | 2014-07-16 | 2014-07-16 | Method and system for database selection |
| PCT/IB2014/001331 WO2016009239A1 (en) | 2014-07-16 | 2014-07-16 | Method and system for database selection |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/IB2014/001331 WO2016009239A1 (en) | 2014-07-16 | 2014-07-16 | Method and system for database selection |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2016009239A1 true WO2016009239A1 (en) | 2016-01-21 |
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ID=51535474
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/IB2014/001331 WO2016009239A1 (en) | 2014-07-16 | 2014-07-16 | Method and system for database selection |
Country Status (2)
| Country | Link |
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| EP (1) | EP3170098A1 (en) |
| WO (1) | WO2016009239A1 (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5983220A (en) * | 1995-11-15 | 1999-11-09 | Bizrate.Com | Supporting intuitive decision in complex multi-attributive domains using fuzzy, hierarchical expert models |
| US20010042060A1 (en) * | 2000-02-18 | 2001-11-15 | Homeportfolio Inc. A Massachusetts Corporation | Attribute tagging and matching system and method for database management |
| US20070083504A1 (en) * | 2005-10-06 | 2007-04-12 | Britt Michael W | Selecting information technology components for target market offerings |
-
2014
- 2014-07-16 WO PCT/IB2014/001331 patent/WO2016009239A1/en active Application Filing
- 2014-07-16 EP EP14762091.8A patent/EP3170098A1/en not_active Withdrawn
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5983220A (en) * | 1995-11-15 | 1999-11-09 | Bizrate.Com | Supporting intuitive decision in complex multi-attributive domains using fuzzy, hierarchical expert models |
| US20010042060A1 (en) * | 2000-02-18 | 2001-11-15 | Homeportfolio Inc. A Massachusetts Corporation | Attribute tagging and matching system and method for database management |
| US20070083504A1 (en) * | 2005-10-06 | 2007-04-12 | Britt Michael W | Selecting information technology components for target market offerings |
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| Publication number | Publication date |
|---|---|
| EP3170098A1 (en) | 2017-05-24 |
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