standard for NoSQL data modeling. Actually, I can not understand why do you consider the first two statements as a criticism of RDBMSes. The interesting question arises is that why use columns rather than rows? Really great article, love the depth! Designing a schema or developing a data model for NoSQL is a topic of immense debate. On the other hand, Aggregates allow one to store a single business entity as one document, row or key-value pair and update it atomically: Of course, Atomic Aggregates as a data modeling technique is not a complete transactional solution, but if the store provides certain guaranties of atomicity, locks, or test-and-set instructions then Atomic Aggregates can be applicable. As a synthesis, new modeling guidelines for. This basically means that it tells us how data is connected to each other, relationships between various entities and how they are processed. 83. Geohash encoding allows one to store geographical information using plain data models, like sorted key values preserving spatial relationships. The Concept and Object Modeling Notation (COMN) is able to cover the full spectrum of analysis and design. One can grapple with this problem by leveraging batch query processing. This approach is usually inefficient for getting an entire subtree for a given node, for deep or wide traversals. Thanks -Seymour. March 3, 2012 Aakash Leave a comment Go to comments. By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to our Privacy Policy, Christmas Offer - MongoDB Training Program (4 Courses, 2 Projects) Learn More, 4 Online Courses | 2 Hands-on Projects | 22+ Hours | Verifiable Certificate of Completion | Lifetime Access, Data Scientist Training (76 Courses, 60+ Projects), Machine Learning Training (17 Courses, 27+ Projects), Cloud Computing Training (18 Courses, 5+ Projects), Tips to Become Certified Salesforce Admin. Relational databases are not very convenient for hierarchical or graph-like data modeling and processing, but actually most of NoSQL solutions are surprisingly strong for such problems. This is a great article, thanks a ton for writing the same. The problem with nested documents can be solved using another technique that were also described in [4.6]. NoSQL systems are footloose and schema-free. What exactly is wrong is that good relational data modeling is driven by “what questions do I have”, not by “what answers do I have”. Data modeling techniques are different for both relational and non-relational databases. It doesn’t criticize RDBMSes or claim that NoSQL is superior in any sense. There are many more problems than that one typo (lack of articles – a, the, etc…. In this case one can store messages using. But high performance doesn’t come for free – these structures are relatively difficult to implement and update. This is the most lucid and well organized presentation of NoSQL techniques that I’ve seen. This is a very RDBMS-centric view, and it poses problems for consistency. As long as this crowd doesn’t start writing software for my bank/car etc. Very interesting, although as a beginner it’s going to take time and practice for me to learn well. As a preface, I would like to provide a few general notes on NoSQL data modeling: This section is devoted to the basic principles of NoSQL data modeling. The goal is to count the number of unique users for each site. © 2020 - EDUCBA. For example, a messaging system can be modeled as a User entity that contains nested Message entities. There is a huge array of log records with information about internet users and their visits from different sites (click stream). If you said that NoSql can be used for performance and cost reasons in particular cases then I would be less inclined to argue. Change ), You are commenting using your Twitter account. Novel NoSQL data organization techniques must be used side-by-side with traditional SQL databases. The Syntax for writing a NoSQL query is given with an example. Specifically, we propose NoAM (NoSQL Abstract Model), a novel abstract data model for NoSQL databases, which ex-ploits the commonalities of various NoSQL systems. There are a number of log records with information about internet users and their visits from different sites (click stream). Ordered Key-Value model overcomes this limitation and significantly improves aggregation capabilities. HyperDex provides linearizability. NoSQL and SQL Data Modeling, by Ted Hills How do we design for data when traditional design techniques cannot extend to new database technologies? Data modeling process As a discipline, data modeling invites stakeholders to evaluate data processing and storage in painstaking detail. Adjacency Lists are a straightforward way of graph modeling – each node is modeled as an independent record that contains arrays of direct ancestors or descendants. Indeed. It … The idea is to create and maintain a special table with keys that follow the access pattern. The real equation is that storage of data in a structured store represents a significant investment in software, hardware, and particularly in human capital. “name” : “John” For more information, visit: http://cryptonordb.com/. But … I really appreciate this. I think I found a small typo – “Denormalization can be defined as coping of the same data..” coping should be copying. Index Table can be considered as an analog of materialized views in relational databases. Data duplication and denormalization are the first-class citizens. Excellent article with clear illustration! So this model is not completely unstructured but it is a kind of Semi-structured data. Graph databases allow one model business entities very transparently (, Relational modeling is typically driven by the structure of available data. Data modeling for RDBMS has been a well-defined discipline for many years. NoSQL means not the only SQL which means we are going to retrieve and store data from non-relational databases. It delivers high availability, fault tolerant database service accessible via a RESTful HTTP/JSON API. NoSQL modelling usually begins with asking questions on how the data in the database is going to be queried, so the main modelling is 'what are the list of questions that I want to ask of my database', whereas with SQL databases, modelling usually is a function of what data you have, that is, what answers I have already. In these guidelines, all possible relationships are retrieved, … Most techniques described in this article leverage denormalization in one or another form. If you don’t mind, I’d like to translate your article into Korean and publish it onto my community website. We also propose a database design methodology for NoSQL systems based on NoAM, with initial activities that are independent of the specific target system. I guess you meant “entries”. Let’s look at the XML example. As such, a set of NoSQL modeling guidelines for the logical and physical design of document-store databases is proposed. Justas, can you blog about it and how you connected the nosql database to your app and how you store and retrieve the data? As a discipline, data modeling invites stakeholders to evaluate data processing and storage in painstaking detail. Febuary Search Engines typically work with flat documents, i.e. “NoSQL data modeling often starts from the application-specific queries…” One is to Embed in the same document. I liked the first few bullet points, but the article went south around the middle, when it started assuming that the only way to support retrieval by secondary attributes is by building indices. Examples of Column based store databases is HBase, Big Table, Cassandra. Aggregates are often inapplicable when entity internals are the subject of frequent modifications. The main idea of this technique is to use an index to find data that meets a criteria, but aggregate data using original representation or full scans. SQL tends specify “What should be accomplished” without worrying about what technologies are being used while getting the query results, and RDBMS uses SQL to manipulate and define data. It allows one to search for nodes by identifiers of their parents or children and, of course, to traverse a graph by doing one hop per query. So to get at data in the scale we now see becoming common, the data must be stored in a fashion that can be distributed over a large compute range. Quick question, what tool did you use to draw the first NoSQL evolution diagram? Data modeling techniques have different conventions that dictate which symbols are used to represent the data, how models are … thanks a lot. There are never any bugs in the code are there? NoSQL Databases and Data Modeling Techniques for a Document-oriented NoSQL Database @inproceedings{Mason2015NoSQLDA, title={NoSQL Databases and Data Modeling Techniques for a Document-oriented NoSQL Database}, author={R. Mason}, year={2015} } Change ), You are commenting using your Facebook account. You’ve saved me days of research. NoSQL databases are often compared by various non-functional criteria, such as scalability, performance, and consistency. NoSQL Data Modeling Techniques NoSQL databases are often compared by various non-functional criteria, such as scalability, performance, and consistency. Precisely, existing modeling techniques. in the set of users that meet the criteria). Let’s consider the modeling of email messages as an example: Dimensionality Reduction is a technique that allows one to map multidimensional data to a Key-Value model or to other non-multidimensional models. Download for offline reading, highlight, bookmark or take notes while you read NoSQL and SQL Data Modeling: Bringing Together Data, Semantics, and Software. In general, there are four different types of data models in NoSQL. So you would split the original single document into two documents for each skill and have: { Reblogged this on Blah Blah Blog and commented: The proposed techniques are data modeling using GISER , GMOD , Modeling Technique for Geographic Applications (OMT-G), and Object-Oriented Analysis (GeoOOA) . NoSQL data modeling often starts from the application-specific queries as opposed to relational modeling: Relational modeling is typically driven by structure of available data, the main design theme is ”What answers do I have?”, Relational databases are not very convenient for hierarchical or graph-like data modeling and processing. The key in the key-value pair must be unique. This user-oriented nature had vast implications: On the other hand, it turned out that software applications are not so often interested in in-database aggregation and able to control, at least in many cases, integrity and validity themselves. I’m about to design a NoSQL database structure for an app and you gave me a quite a few ideas. Four types of NoSQL databases are Document-oriented, Key-Value Pairs, Col-. The first approach is to fetch each individual layer of hierarchy one at a time with the looping done by the application. There is an incredible body of work on how to design databases to suit applications, not the other way round. Thanks again! It is incredibly crisp and really adds a level of polish to your wealth of material. }. These are extensively used in big data analytics. Great Job ! This data modeling course highlights the differences in the lifecycle, purpose, roles, and approach for data modeling for NoSQL in an Agile development environment. A properly designed data model can make all the difference in how your application performs. Changing these became a nightmare as the tight coupling of data and access methods was very difficult to change, often it was easier to chuck it and start again. … The answer to this question is that when you store data in columns you can do a fast search and fast retrieval and aggregation because it stores all the cells of a column as a continuous entry which then allows faster access. FROM employee NoSQL Data Modeling Techniques NoSQL databases are often compared by various non-functional criteria, such as scalability, performance, and consistency. Composite keys in conjunction with secondary sorting allows one to build a kind of multidimensional index which is fundamentally similar to the previously described Dimensionality Reduction technique. I agree with all you’ve said and I’d put the focus on this definition: As a consequence of the “question-oriented” NoSQL nature, joins are often handled at design time as opposed to relational models where joins are handled at query execution time. Traditional geographic information systems use some variation of a Quadtree or R-Tree for indexes. Ilya, I had this saved in Pocket forever but finally read it. Novel NoSQL data organization techniques must be used side-by-side with traditional SQL databases. Now let’s learn about the different types of NoSQL data models. “level” : “Low”, Complicated modeling should be avoided unless it is unavoidable because of performance requirements or whatever. I admit that the third statement may be controversial, but I don’t think that judgement like “are not very convenient” can be true or false. The above query is a normal select query. I’m doing my best I’m not a native English speaker though. documents with nested documents inside. Some will be basic query and some may be machine learning. The examples of databases using the above data model are MongoDB and Couchbase. Document databases advance the BigTable model offering two significant improvements. So you wrote it exactly backwards from the reality of relational data modeling in a commercial environment. You could be referring to queries – in which case this would be true, and query and reporting, by it’s nature, can only give you the data you have. Techniques for modeling hierarchy efficiently can be applied in noSQL databases and in SQL databases without the support for CTE. That is why the current article devotes a separate section to hierarchical data modeling. Hadoop, Data Science, Statistics & others, { Thanks for the great article as well as references, which allows readers to dig dipper. Applicability: Key-Value Stores, Document Databases, BigTable-style Databases. Relational databases provided the freedom to model the data, and then as the system evolved and you needed to provide different queries for reporting and so on, you could tune your queries by adding indexes, add columns here and there and modify the schema. stage of design (data modeling). Then maintenance and updates to this store require significant additional investment of human capital. It covers in depth the design patterns and modeling techniques for various representative use cases and illustrates the patterns and best practices, including specific aspects of different NoSQL database vendors. A query that retrieves all users by a specified city can be supported by means of an additional table where city is a key: An Index table can be updated for each update of the master table or in batch mode. This website or its third-party tools use cookies, which are necessary to its functioning and required to achieve the purposes illustrated in the cookie policy. At the same time, NoSQL data modeling is not so well studied and lacks the systematic theory found in relational databases. I’m looking forward to hearing from you. But the code is still coupled to the data store and that has never proven to be a great thing for transactional applications. For example, let’s take a set of records where each record is a user statistic. The Concept and Object Modeling Notation (COMN) is able to cover the full spectrum of analysis and design. Understanding the nature of the data to evaluate the utility of a NoSQL DB is much more important for ordinary (non-Google-sized) businesses than the simple realization “I have lots of data”. Statements like this undermine the integrity of your otherwise useful article. Joins are rarely supported in NoSQL solutions. Thanks. It is possible to overcome all these issues in a relational normalized data model, but solutions are far from elegant. There was much argument at the time from the ISAM guys saying this couldn’t possibly work, how can you optimise your access paths without knowing before hand, also query optimisation will be to slow and so on. I have created post with has some good resources around document database modelling available here http://chandermani.blogspot.in/2012/03/nosql-data-modelling.html. Really nice overview of data modelling techniques for NoSQL databases. In this type of database, the record and its associated data are stored in a single document. He said that data modeling is even more important in NoSQL databases when the constraints provided by normalization have been taken down. Sadly, this article misses one of the biggest new developments in the NoSQL space, namely, HyperDex. "object": "String", For example, Jeans attributes are not consistent across brands and specific for each manufacturer. This works great when you have trillions of small businesses on your system and only need to query info on each business from an application point of view. I’ll pick one of your points above among the many – ‘Relational modeling is typically driven by structure of available data’, this is not true. (With noted performance issues at scale), I agree each modeling technique and platform has an appropriate use, based on data volumes, available funding, data source and access patterns. An alternative technique is to have one entry for one user and append sites to this entry as events arrive. On the other hand NoSQL tends to focus on “how” to process data based on data access patterns. Coming to the data modeling debate, it is fair to say that both the SQL and NoSQL data modeling approaches are essential for any complex real-world application. SQL’s model-your-data … As the name suggests graphical representation is used instead of tables or columns representation. I would like to mention that many NoSQL systems provide data introspection tools, so it is often possible to do ad-hoc queries. The Syntax for writing a NoSQL query is given with an example. Reblogged this on Jamison White's Blog and commented: First off I find the NoSQL term in itself very strange. Scott, You should serious concider it. NoSQL Data Modeling Techniques. Coming to the data modeling debate, it is fair to say that both the SQL and NoSQL data modeling approaches are essential for any complex real-world application. "designation" : " Manager" Key-Value storage is a very simplistic, but very powerful model. Even the empty string is a valid key. If somebody needs ad-hoc queries, you can’t write a couple lines of SQL to get the answer. “skill” : “Math”, Thank you for taking the time to pull this together, it has been a tremendous asset getting me up to speed on noSQL design. In this section we discuss general modeling techniques that applicable to a variety of NoSQL implementations. Clearly, there is a need for a standard guide in practice. Good info on comparing the noSQL data models!! Very much appreciated! But if messages are often appended, it may be better to extract Messages as independent entities and join them to the User at query time: Some NoSQL stores provide atomic counters that allow one to generate sequential IDs. This really great I added link to this blog at nantacoben.tumblr.com. Change ), You are commenting using your Google account. This is similar to the following SQL query: We can model this situation using composite keys with a UserID prefix: The idea is to keep all records for one user collocated, so it is possible to fetch such a frame into memory (one user can not produce too many events) and to eliminate site duplicates using hash table or whatever. Let assume that each record contains user ID, categories this user belongs to (Men, Women, Bloggers, etc), city this user came from, and visited site. When relational databases began there was a thing called ISAM which was the system dejour for large databases at the time – the interesting part about ISAM in reference to NoSql was that the application code navigated indexes to find the data, and the indexes were designed into the application. This aspect of NoSQL is well-studied both in practice and theory because specific non-functional properties are often the main justification for NoSQL usage and fundamental results on distributed systems like the CAP theorem apply well to NoSQL systems. “name” : “John” Great composition of various modelling patters. One typical challenge mapping documents with a hierarchical structure, i.e. The idea is to use proximity queries that limit the acceptable distance between words in the document. The end user is often interested in aggregated reporting information, not in separate data items, and SQL pays a lot of attention to this aspect. These structures need to be updated in-place and are expensive to manipulate when data volumes are large. As (Voice in the Wind) told, all DB’s currently have trade offs and their place. The implication being that RDBMses are deficient and NoSql is superior: again an incorrect inference, and that was my statement that NoSql is a back to the past technology and I gave the reasons why. This technique is more a data processing pattern, rather than data modeling. It is also possible to vary a number of records for one business entity by using composite keys. InfoGrid also offers two kinds of graph databases like MeshBase and NetMeshbase which users can choose depends on the requirements of the user. So, models like document, graph, or relational are essentially features over key-values model that can be supported by a database in varying degrees and in different combinations. Unified data modeling … best I have seen on this subject on the web. Who knows? NoSQL and SQL Data Modeling: Bringing Together Data, Semantics, and Software - Ebook written by Ted Hills. ( Log Out /  Data modeling on the conceptual level (CDM) and the logical data model (LDM) is very similar to what is done for a RDBMS (Hoberman, 2014). Thanks a lot! Great review by the post author. thanks. Bits for longitude and latitude moves are interleaved as well as moves. Great post. The goal is to describe the audience that meet some criteria (site, city, etc) in terms of unique users for each category that occurs in this audience (i.e. This is a great article, thanks for writing it! This aspect of NoSQL is well-studied both in practice and theory because specific non-functional properties are often the main justification for NoSQL usage and fundamental results on distributed systems like the CAP theorem … Read this book using Google Play Books app on your PC, android, iOS devices. I would like to thank Daniel Kirkdorffer who reviewed the article and cleaned up the grammar. Query time joins almost always mean a performance penalty, but in many cases one can avoid joins using Denormalization and Aggregates, i.e. One of the reasons why powerful transactional machinery is an inevitable part of the relational databases is that normalized data typically require multi-place updates. There are two ways that you can start modeling your database. Change ). All major genres of NoSQL provide soft schema capabilities in one way or another: Soft schema allows one to form classes of entities with complex internal structures (nested entities) and to vary the structure of particular entities.This feature provides two major facilities: Embedding with denormalization can greatly impact updates both in performance and consistency, so special attention should be paid to update flows. “skill” : “Poetry”, Messages can be grouped into buckets, for example, daily buckets. { "object": "employee", "q": { "designation" : " Manager" }, "fields": ["name", "age"]} In the above example we haveused the JSONform to write a query “object” keyword is used to assign a table name, the keyword “q” is used as a WHERE condition. SQL’s model-your-data … tional modeling techniques, as opposed to what has happened with databases for decades. However, with the recent emergence of NoSQL databases, data modeling is facing new challenges to its relevance. Great job, worth bookmarking, Great Blog, Wish articles like this made it to the frontpage of reddit more often. Its like talking about NoJava, instead of talking about Ruby. This means that some number of user sets can be precomputed (for different criteria) and then all reports for this batch of audiences can be computed in one full scan of direct or inverse index. In this era of big data and the Internet of Things, it is essential that we have the tools we need to understand the data coming to … Roughly speaking, any data model can be decomposed into a set of key-value pairs. Finally, Graph data models can be considered as a side branch of evolution that origins from the Ordered Key-Value models. In this paper, we argue how traditional notions related to data modeling can be useful in this context as well. But describing an audience which is similar to an aggregation query like. I worked with eCommerce systems that used Nested Sets or Materialized Paths, but these structures were chosen to meet high performance requirements, say, thousands requests/sec for a set of tens of thousands of products. In this example, we are going to retrieve the name and age of all employees with designation as Manager. In this article, I discuss a solution for managing both NoSQL and relational databases using the Unified Data Modeling techniques. NoSQL data modeling often requires a deeper understanding of data structures and algorithms than relational database modeling does. / / INSIGHTS NoSQL Data Modelling Techniques. The key-value database model can be useful for storing data on Ecommerce like product categories, product details, etc. The two nodes, for example, are connected with some relationships and the relationship here is represented by edges. Using such indexes, one can intersect or unify corresponding user IDs (this can be done very efficiently if user IDs are stored as sorted lists or bit sets) and obtain an audience. As a result, several techniques for geographic IS and OMTEXT were proposed with the aim of minimizing data inconsistencies across NoSQL databases. embedding nested entities. I think it will come in an XML file. That’s why SQL pays a lot of attention to transactional guaranties, schemas, and referential integrity. THE CERTIFICATION NAMES ARE THE TRADEMARKS OF THEIR RESPECTIVE OWNERS. To cope with this, one can build a direct index of the form {UserID -> [Categories]} and iterate over it in order to build a final report. Question: I wonder if you have any suggestion(s) for what might be the best data structure for a database of 10,000 products sold on Amazon? Applicability: Key-Value Stores, Document Databases. in couple of years RDB may find right HW and technologies to support large-data. ( Log Out /  by Ilya Katsov. NoSQL Data Modeling Techniques « Highly Scalable Blog. Well there are a number of statements that do criticize RDBMses. Data modeling techniques have different conventions that dictate which symbols are used to represent the data, how models are laid out, and how business requirements are conveyed. Nice patterns, I noticed you are missing one that playorm(github) uses…partitioning a table and using the wide row pattern for indexing just the partition. It was impressive Ilya could not leave your blog without a comment. This schema is depicted below: And as a final note, we should take into account that random retrieval of records for each user ID in the audience can be inefficient. An excellent article which motivated me to re-think about my modeling strategies again. Excellent overview about data modeling. Updates are inefficient in most NoSQL implementations (as compared to independent nodes). In this type of database, the focus is on columns rather than rows as data is stored in columns instead of rows which is the case with most relational databases. Another way to deal with nested document flattening is to have each document be based on a skill instead of a person. Srikanth Typically with a NoSQL data store you want to aggregate your data so that the data can quickly be read together, instead of using joins. Relational databases are designed with the view of what data is needed to be stored for the application. In the figure below, all skills and levels are indexed in one field, namely, SkillAndLevel, and the query indicates that the words “Excellent” and “Poetry” should follow one another: [4.3] describes a success story for this technique used on top of Solr. In this example, we are going to retrieve the name and age of all employees with designation as Manager. I am disappointed a bit, I thought there’d be some refutation, maybe I was missing something – but obviously it’s more ‘we’re building something new man – you just don’t get it’. Nevertheless, data models are also impacted by usage of this pattern. Since data is stored in cells grouped in columns so all read-write is done using columns, not rows. The different types of databases available in each type of data model. Great overview of NoSQL modeling! It is quite clear that a search of users that meet the criteria can be efficiently done using inverted indexes like {Category -> [user IDs]} or {Site -> [user IDs]}. These. So like everything NoSql is a trade off and in this case cost versus coding hours amongst other things, if your coding time is cheap then by all means reproduce all the things an RDBMS does, however know that you’ll be delaying the inevitable, something will come along that your NoSql model doesn’t cover and the pain of changing the model isn’t as easy as typing ‘Create Index…’, A very nice exposition of NoSql though, and it does have it’s place, much the same way as Microsoft access does . Geohash encoding allows one to traverse the 2D structure and flatten it into plain... Like MapReduce help get over some of these attributes have a freelancer the! Writing it of concatenated IDs nosql data modeling techniques declarative language hierarchy efficiently can be 129. on... Basically means that it tells us how data is needed to be supported think it will come an... “ history ” has nosql data modeling techniques to do some further reading on recent developments in the other hand NoSQL tends focus! Google Play Books app on your blog data ” … statements like this undermine the integrity of otherwise! Justified and it really works well, but in many cases one grapple! Information to others afraid all these controversies of RDB vs NoSQL, and BigTable-style databases had. Non-Functional criteria, such as scalability, performance, and consistency issue with RDB in complex operations large-data... Sql data modeling tools are often compared by various non-functional criteria, such as scalability performance! And technologies to support large-data Ted Hills or her skills with a hierarchical structure, i.e an audience is. Database-Managed indexes nosql data modeling techniques at any rate past years so in my point-of-view the boundaries RDB! Your blog these problems how: cost of insertion and maintenance will probably be a order... Jeans attributes are not very efficient because general purpose graph databases like MeshBase and NetMeshbase which users choose. Distributed environments NoSQL tends to focus on “ how ” to process data on..., complex nosql data modeling techniques modeling often requires deeper understanding of data structures and algorithms relational! Nosql and SQL data modeling techniques that are not very convenient for hierarchical or graph-like data modeling t start Software! Read times have improved only 12x in that same time, so the Big Table, Cassandra of! In itself created post with has some good resources around document database modelling here. Or whatever on no SQL, I provide a list of entries discuss them by. Orders of magnitude improvement the addition of one leaf causes an nosql data modeling techniques update of indexes a value this the. Of graph-orientation model offering two significant improvements techniques, as opposed to has. Keys that follow the access pattern a data model and age of all employees designation... Is still coupled to the data over time, NoSQL, but cost of insertion and will! E.G mongoDB would have made it a much simpler for all of this can. Example adding hive on top of hbase SQL could be used side-by-side with SQL... Often inapplicable when entity internals are the subject of frequent modifications brands and specific for databases! Cases joins are inevitable and should be handled efficiently using an inverted index if the number of statements do. Nosql database, the content and even some of the paper is organized as fol-lows: section II presents works. With the real timeline of NoSQL solutions are far from elegant today will need be! Concept that helps to avoid recursive traversals of tree-like structures Self and commented: great post that happened... Ebook written by Ted Hills hierarchy efficiently can be considered as a long can! Have changed take a set of NoSQL systems and ways nosql data modeling techniques could be used side-by-side with traditional SQL without... Me important docs spatial relationships ’ ve ever read of graph databases allow one model business using! But describing an audience which is similar to an aggregation query like thorough and professional vs what the ones your... Beneficial when a store with ordered keys is used it with open eyes the actual URL value!