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70-768 - Developing SQL Data Models - BrainDump Information

Vendor Name : Microsoft
Exam Code : 70-768
Exam Name : Developing SQL Data Models
Questions and Answers : 37 Q & A
Updated On : December 11, 2018
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70-768 exam Dumps Source : Developing SQL Data Models

Test Code : 70-768
Test Name : Developing SQL Data Models
Vendor Name : Microsoft
Q&A : 37 Real Questions

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Microsoft Microsoft Developing SQL Data

Microsoft Azure SQL Database nears parity with SQL Server | killexams.com Real Questions and Pass4sure dumps

SEATTLE -- After a two-yr building effort to tackle its technical limitations, Microsoft Azure SQL Database is finally poised to become a more workable option to on-premises SQL Server techniques for clients who want to shift database purposes to the cloud.

Microsoft's R&D work is culminating in a flurry of latest facets and product choices. for example, the vendor on Dec. 1 plans to launch a high-end edition of its Azure SQL Database Managed example cloud platform for company functions with heavy-responsibility I/O necessities. Managed illustration is an implementation of Microsoft Azure SQL Database it really is pretty much functionally comparable to SQL Server, based on Microsoft, which launched a typical-aim version of the carrier at the start of October.

At flow Summit 2018, Microsoft additionally made obtainable a public preview of its machine getting to know features utility operating within the core Azure SQL Database platform. That follows preview releases in October of two other new applied sciences: a Hyperscale provider tier that eliminates Azure SQL Database's 4 TB restrict on database size, and an Accelerated Database restoration feature built to velocity up the system of convalescing databases after a gadget failure.

Hyperscale supports databases with up to one hundred TB of statistics -- an increase that changed into welcome news to Azure SQL Database consumer Mark Freeman, a senior database administrator at tax, audit and management consulting capabilities business BDO world.

"at this time, we're confined to 4 TB databases, and they just type of blew the roof off of that," Freeman observed at the convention.

PASS Summit 2018 in Seattle Updates to Azure SQL Database had been designated and discussed at circulate Summit 2018. Separation coverage on Azure databases

Brussels-based mostly BDO runs tons of of databases on Microsoft Azure SQL Database, observed Freeman, who works at the company's workplace in Columbus, Ohio. but the IT team had to cut up up greater databases because of the PaaS technology's old dimension restriction, he added. subsequently, operational facts for individual international locations will also be spread throughout as many as seven separate databases, in line with Freeman.

at this time, we're limited to 4 TB databases, and that they simply variety of blew the roof off of that. Mark Freemansenior DBA, BDO global

"Now we can put it all collectively in a single area with no need to be concerned about recovering the entire databases," he said.

Azure SQL Database also may additionally now be in a position to tackle older functions that BDO runs on Microsoft's SQL Server on Azure digital Machines platform because of their measurement, Freeman spoke of. The latter know-how is cloud-based, too, but it's an IaaS providing that requires database directors (DBAs) to deal with configuration, patching and different administration projects that Azure SQL Database automates.

earlier, DBAs looking to migrate existing purposes to the cloud typically had to use SQL Server on Azure digital Machines. Microsoft Azure SQL Database become primarily geared to run new cloud-native purposes as a result of the database size obstacle and its lack of help for some key SQL Server aspects, such because the SQL Server Agent job scheduler. That dampened its enchantment to the installed base.

"We knew there have been some challenges with Azure SQL Database," referred to Rohan Kumar, corporate vice chairman of engineering for Azure facts functions and SQL Server at Microsoft.

speaking in the opening keynote session at move Summit 2018, Kumar introduced that Azure SQL Database Managed instance aims to cut back the "friction" on cloud migrations that latest users encountered. SQL Server applications can be moved to a Managed illustration ambiance with none changes, he mentioned. And the high-conclusion Managed illustration company critical version will permit users "to run their most mission-important SQL Server workloads in Azure," Kumar claimed.

a familiar feel for SQL Server clients

The Managed instance know-how is still a work in progress, referred to Denny Cherry, founder and predominant advisor at Denny Cherry & pals Consulting in Oceanside, Calif. but in an interview on the convention, Cherry mentioned he expects person demand for Managed example deployments to increase once the business essential provider tier is accessible.

"it's form of the SQL Server you be aware of," referred to Mike Walsh, president of heterosexual route IT solutions, a SQL Server consulting capabilities company in Milton, N.H.

The Managed example implementation of Microsoft Azure SQL Database will also be expensive, Walsh mentioned throughout a conference session. On Microsoft's site, he set up a sample configuration with a compute can charge of $one hundred fifty,000 monthly for the highest number of eighty vCore logical CPUs. however clients can get discounts of as much as 55% if they convert an current SQL Server license to the cloud equipment, Walsh spoke of.

Beautycounter, a multilevel advertising and marketing company that sells skincare, make-up and bathtub items, runs SQL Server on the AWS cloud in its place of Azure. during the past, the Amazon Relational Database carrier (RDS) for SQL Server offered greater functionality and options than Microsoft Azure SQL Database did, talked about Steve Rezhener, a database engineer at Beautycounter, which is based in Santa Monica, Calif., and formally referred to as Counter brands LLC.

Azure SQL Database Managed example does not fully trade that, Rezhener pointed out in an interview on the conference. "but as a minimum the points are on par with RDS," he delivered. "It looks like or not it's on-premises SQL Server."

At flow Summit 2018, the annual convention of the knowledgeable association for SQL Server person group, Microsoft additionally launched the 2nd release of SQL Server 2019 below its neighborhood technology Preview software. CTP 2.1 adds the means to run R and Python purposes within the huge information clusters that SQL Server 2019 supports, plus different new points. Microsoft's aim is to liberate a preview every month, Kumar referred to.


advancements Coming to Azure SQL, SQL Server 2019 Preview | killexams.com Real Questions and Pass4sure dumps

news

advancements Coming to Azure SQL, SQL Server 2019 Preview
  • with the aid of Kurt Mackie
  • November 08, 2018
  • A raft of improvements are coming to Microsoft's database products, together with migration aid to Azure SQL Database, Apache Kafka help on Azure event Hubs, Azure SQL data Warehouse improvements and yet a different preview of the arriving SQL Server 2019 product.

    Microsoft introduced the improvements at this week's flow Summit event for database directors and builders.

    SQL Server 2019 CTP 2.1SQL Server 2019 remains at the preview stage, even though it's now reached neighborhood expertise Preview (CTP) 2.1, in response to Rohan Kumar, Microsoft's company vice chairman for Azure records, within the announcement. Microsoft is touting constructed-in aid for Apache Spark and the Hadoop distributed File device within the coming SQL Server 2019 product.

    The latest preview of SQL Server 2019, specifically CTP 2.1, provides guide for deploying Python- and R-primarily based applications on clusters. It brings the capacity to location a "buffer pool in persistent reminiscence," which is concept to speed up I/O operations. there's also enhanced diagnostics for troubleshooting lengthy-running queries that have gotten blocked, amongst different perks.

    yet another feature that may be coming to SQL Server 2019 in a future preview unlock should be a brand new "Accelerated statistics recovery" feature, Kumar mentioned.

    Hybrid and Migration SupportKumar mentioned that Microsoft has been "architecting for hybrid" to guide purchasers that plan to run "information workloads in on-premises [servers] and in the cloud." To that end, Microsoft has been making it more convenient for SQL Server users emigrate toward Azure SQL features.

    Kumar pointed to the Azure SQL Database Managed example provider as a at present obtainable solution for some agencies working SQL Server 2008 and SQL Server 2008 R2, which each will fall out of "extended assist" on July 9, 2019, fitting unsupported products. Azure SQL Database Managed example, which is a provider managed with the aid of Microsoft, is described as being a space in Microsoft's datacenters it truly is "committed on your needs and not shared with another purchasers," according to this Microsoft blog put up. Azure SQL Database Managed instance makes use of the SQL Server 2017 commercial enterprise edition, which has "backward compatibility with SQL Server 2008 and more recent" server items, Microsoft indicated.

    Microsoft is also planning to add a new business vital tier to the Azure SQL Database Managed example carrier for agencies running "mission-critical company apps with excessive I/O requirements." This enterprise important tier is expected to attain "well-known availability" (industrial unencumber) on "December 1," in keeping with Kumar. it will also have a lower-can charge "reserved means" pay as you go choice that'll be in response to a "1 or three-yr term commitment" by businesses, he delivered.

    Azure experience Hubs for Apache KafkaMicrosoft introduced on Wednesday that Azure adventure Hubs for Apache Kafka has reached conventional availability.

    essentially, Microsoft added support for operating the Apache Kafka open supply platform on Azure event Hubs, which is Microsoft's "cloud-native serverless answer" for dealing with "significant-scale, real-time movement ingestion." Microsoft is touting the use of Apache Kafka on Azure in this way as a result of organizations won't have to trouble with configuring it, nor will they ought to manage servers or networks. corporations might not need to trade their Kafka-based mostly functions to make it work with Azure event Hubs, Microsoft promised.

    Azure SQL records WarehouseMicrosoft had an awful lot to assert in an announcement about development to its Azure SQL records Warehouse product, which supports running queries across "petabytes of facts." The "Gen 2" version of Azure SQL information Warehouse become launched back in April, the announcement cited.

    A coming "Workload significance" characteristic will help optimize question execution on Azure SQL information Warehouse. it is going to let companies "use a single SQL statistics Warehouse database to greater correctly run diverse workloads, getting rid of the complexity of separate records warehouses for every answer," Microsoft explained. The Workload magnitude characteristic can be attainable "later this year at no additional cost."

    a brand new Row-stage safety function of Azure SQL records Warehouse has now reached universal availability reputation, Microsoft introduced on Wednesday. Row-degree safety gives businesses more suitable handle over who can entry records, in keeping with the facts's location in rows of tables. This feature is supported by way of both "SQL authentication and Azure active directory authentication," the announcement noted. groups create safety policies in line with "filter predicates" to handle entry, besides the fact that children Microsoft plans so as to add aid for "block predicates" quickly. Row-stage protection is presently obtainable in "just a few" Azure regions, nonetheless it's anticipated to be deployed international "in the subsequent two weeks." it will be attainable at no extra cost, the announcement indicated.

    Microsoft delivered management assist to Azure SQL information Warehouse by the use of Azure advisor and Azure monitor, in line with a Wednesday announcement. each of these tools are "configured by means of default" to work with Azure SQL records Warehouse.

    Azure advisor now has an "Adaptive Cache" characteristic for picking when to scale the cache. It additionally has a "desk Distribution" feature for addressing workload efficiency issues. Microsoft introduced a "Tempdb" function to Azure advisor in order that IT professionals can "take into account when to scale and configure useful resource courses." Azure display screen now shows "close precise-time metrics in the overview blade" for Azure SQL facts Warehouse, the announcement indicated.

    additionally, Azure computer screen now has a "Diagnostic Logs" skill that may also be configured to reveal "historical question performance troubleshooting" suggestions, in line with a Wednesday announcement. These diagnostic log views are comparable to what may also be seen with the current Dynamic administration Views strategy, however interestingly they don't seem to be as constrained. as an example, the announcement explained that "DMVs have a limit of 10,000 rows that can comfortably be handed for intensive enterprise statistics warehouse workloads with heavy question pastime." 

    developers now have entry to a preview of a "SQL Server statistics device" in visible Studio, which is bringing change management support to Azure SQL Server statistics Warehouse, in line with a Wednesday announcement. it's a huge deal for here reasons, according to the announcement:

    at present, trade administration and deployment for SQL DW is a non-trivial effort the place clients must construct SQL and PowerShell scripts. This becomes an unmanageable experience as contemporary records warehouse solutions can have over lots of of data pipelines and thousands of database objects. This problem is exacerbated as records warehouse deployments customarily have numerous environments for development, assessments, and production.

    Microsoft is promising that the SQL Server facts device in visual Studio will add "a first class business-grade development adventure on your up to date information warehouse," with out a more want for guide scripting.

    concerning the creator

    Kurt Mackie is senior news producer for the 1105 commercial enterprise Computing neighborhood.


    a straightforward way to Modernize Your SQL Server atmosphere | killexams.com Real Questions and Pass4sure dumps

    Joey on SQL Server

    a straightforward strategy to Modernize Your SQL Server atmosphere

    There used to be few decent alternatives for a DBA with a bunch of systems stuck on SQL Server 2008. however thanks to one convenient trick, agencies on aging infrastructure can take advantage of Microsoft's up to date records platform.

  • by means of Joey D'Antoni
  • eleven/07/2018
  • usually during this column, I tell you lots about new and exciting elements which are arriving to SQL Server and the broader Microsoft data platform. To take potential of those new aspects, nearly at all times, you deserve to be on the newest unlock of SQL Server or possibly one version again.

    a extremely contemporary of instance of this includes the infamous SQL Server message 8152 error:

    Msg 8152, level sixteen, State 30, Line 13String or binary records can be truncated.The remark has been terminated.

    in case you've worked with SQL Server for any period of time, you have got probably considered this error. it's conveniently useless at helping you troubleshoot what cost caused the error. thankfully, our chums on Microsoft's Tiger group had been aware of how painful this became to developers and applied a repair in SQL Server 2017 cumulative replace 12 (which is also coming quickly to SQL Server 2016) that returns to you the table name, column and offending information in question. With this new fix, you could see:

    Msg 2628, degree 16, State 1, Line 30String or binary statistics could be truncated in desk 'AdventureWorks2016CTP3.dbo.myTable', column 'myString'. Truncated value: lengthy String of boring text '.

    note that you'll need to use hint flag 460 to enable this messaging (Microsoft didn't need to ruin current functions that expected this message).

    here's the seize: if you're nonetheless running SQL Server 2014 or older, you're going to possible by no means see this fix returned-ported into your database engine.

    while I used this error as an example because it's been an issue for thus long, there are a lot of different facets that have been recently added to SQL Server which are handiest on the newest releases of the platform. a few examples encompass the query keep, computerized tuning and adaptive query processing.

    you are doubtless reading this and announcing, "we've a bunch of legacy apps from small utility carriers who may not guide SQL Server 2012, lots much less a preview liberate of SQL Server 2019. Am I ever going to get to play with these new toys?"

    neatly, here is the place the one convenient trick comes in. At this fall's Ignite convention, Microsoft introduced full aid for lengthy-term use of the compatibility stage alternative. Compatibility level is a database property that determines not best purposeful behavior, but also question optimizer conduct for a given database. historically, this property has been used as a cease-gap measure while upgrading a database engine version, used for a short while, earlier than relocating to the latest stage.

    relocating to the latest compatibility stage may still all the time be a intention on your utility. there are many efficiency enhancements in well-nigh each new unencumber that are blanketed through the compatibility stage. youngsters, this may additionally now not be feasible for all applications, especially third-celebration applications where you do not personal the supply code.

    The explanation for this is that a big possibility of upgrading your SQL Server is your question execution plans changing for the more severe and degrading your software efficiency. Now, Microsoft has invested in technologies comparable to auto-tuning to mitigate such dangers, but it surely also acknowledges that purchasers could need to live on an older compatibility stage for the life of their legacy application. This potential in case you see plan changes, that you may file a aid ticket with Microsoft help to work with the client to isolate the basis trigger and unravel it. moreover, Microsoft will help carriers circulate their functions to more recent releases of SQL Server.

    Microsoft's new take on database compatibility stage has resulted in adjustments within the product's documentation, namely on Compatibility tiers and SQL Server improvements, using Compatibility level for Backward Compatibility and most beneficial Practices for upgrading Database Compatibility level. right here, Microsoft deems compatibility level to be "a valuable device to aid in database modernization, by using enabling the SQL Server Database Engine to be upgraded, while conserving connecting functions [in] functional repute by way of conserving the same pre-upgrade database compatibility stage. provided that the software doesn't deserve to leverage enhancements that are only accessible in a higher database compatibility stage, it is a sound method to upgrade the SQL Server Database Engine and keep the previous database compatibility stage."

    It also adds, "for brand new development work, or when an current software requires use of new features, in addition to performance advancements performed within the query optimizer space, plan to upgrade the database compatibility level to the newest purchasable in SQL Server, and certify your application to work with that compatibility degree."

    it be a clear exchange from no longer so long ago, which means Microsoft realizes the unstated hero feature of SQL Server is backward-compatibility, and has invested in supporting that stance to mitigate upgrade dangers.

    while here's an excellent exchange from Microsoft, you still have to contend with impartial application companies (ISVs), a lot of whom will aid more recent releases of SQL Server, but simplest if you improve the edition of your application application. a good example of here's SharePoint Server 2013, which explicitly handiest helps up to SQL Server 2014. if you desired to flow to a greater contemporary release of SQL Server and have aid from Microsoft for SharePoint, you might deserve to improve to SharePoint Server 2016.

    while RDBMS enhancements are customarily dealt with by means of the infrastructure and DBA agencies of an IT firm, application utility improvements are more frequently handled through the enterprise unit that owns the utility, which constantly increases the quantity of scrutiny. If the enterprise has closely personalized the software, this could make the app-upgrade manner greater challenging.

    when you are a DBA who has a bunch of systems caught on SQL Server 2008, what are you to do? the primary component be sure you do is discuss this new Microsoft position with your management, as that may be the primary hurdle to move before going down the course of a modernization project. second, you should definitely contact your key utility companies about each their assist for more recent SQL Server releases, as well as their stance on using compatibility degree for his or her functions.




    Killexams.com 70-768 Dumps and Real Questions

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    70-768 exam Dumps Source : Developing SQL Data Models

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    Q&A : 37 Real Questions

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    Developing SQL Data Models

    Pass 4 sure 70-768 dumps | Killexams.com 70-768 real questions | [HOSTED-SITE]

    Ruby on Rails: SQL Database & Models | killexams.com real questions and Pass4sure dumps

    What is a database?

    Hmmm... The first thought that comes to my mind is “something” that stores data, information.

    But this “definition” is quite imprecise! An array, a hash, a linked list, or any data structure can be “something” that is able to store data.

    When you turn off the computer, you lose every data values that were stored in that array (the same as all data structures). So it’s not a good idea to store all my precious data.

    MY PRECIOUS DATA

    We need to solve two problems here:

  • Store data and get it anytime we want.
  • Store data in an organized and structured way, so we can get it in an easy way.
  • Should I store all the data in a notepad? Just put all the information inside it separated by commas, save the txt file, and done. Now I can open it and get all the data I want. We can store data and get it anytime… problem solved!

    We solved this problem, but we missed the other. Now all the data is stored and we don’t lose it. But not well-structured in the file. We need the rule to store and get data in an organized and well-structured form.

    Let’s think about how can we organize the data in a well structured way.

    What about organizing all the data in tables?

    So, what we have here: We have the table’s header (columns name: First Name, Last Name, Address, etc) and it’ll have values that we’ll store. For example, if we want to store the string “Mickey” (the value), it’ll be stored in the “First Name” column.

  • Table: let’s say People
  • Columns: First name, Last Name, Address, etc
  • Rows: in this case, we can say that a row can be a person with, for example, first name “Mickey”, last name “Mouse”, address “123 Fantasy Way”, etc.
  • Fields: all data stored in the database.
  • And now we have a well-structured way to store data: Table way!

    How about get, delete, insert, and update data?

    We’ll use SQL language (I’ll not mention NoSQL world!) to manipulate data. Let’s get the basics!

  • GET: if we want to get all data (person) from People table, we need to select it from that table.
  • The (*) symbol means that it will select all columns from People table. If we can get all columns, we can specify which columns we need for this select.

    2. DELETE: we want to delete all data from our People table.

    But it’s not common to delete all data from a table. We usually use a condition to delete, like “I want to delete all people under age (less than 21 years old)”. We will learn it later in this post!

    3. INSERT: we will insert/store data into the table.

    or we can specify which columns we want to insert data.

    4. UPDATE: we have stored data, but we want to update it.

    Using conditions in our queries

    Now we can use SQL language to query (select, delete, insert, update) data.

  • But if we want to delete just records with last name Kinoshita?
  • Or if we want to update a specific person with first name Leandro and last name Kinoshita?
  • Or just select all data from people table and sorted by age from younger to older?
  • Yeah, we use conditions like where and order by and operators like or and and. Let’s see some examples:

  • Deleting all records from people table with last name Kinoshita.
  • Updating all records from people table with first name Leandro and last name Kinoshita.
  • Selecting all records from people table but order by age. (in ascending order → ASC)
  • Relationship between tables

    We know how to execute queries (with or without conditions). Let’s understand how the tables’ relationship works.

  • One to One (1–1): it’s about a relationship between two tables in which one can only belong with the other. e.g. A person has one passport and that passport belongs to that specific person. So in this example, we have table People, table Passports and a 1–1 relationship.
  • One to Many (1-n): it’s about a relationship between two tables in which a record from one table can reference many records from another. e.g. Imagine an e-commerce platform: users, orders, products, payments, etc. A user can have many orders, and each order belongs to that specific user. So in this example, we have table Users, table Orders, and a 1-n relationship.
  • Many to Many (n-n): it’s about a relationship between two tables in which a record from one table can reference many records from another. And a record from another can also reference many records from the one. e.g. We have again the e-commerce platform: we divide products into categories. A category has many products (Category Technology has many products like cell phones, notebooks, etc) and a product can belong to many categories (Product Cellphone belongs to Technology and Electronics Categories). So in this example, we have table Products, table Categories, and an n-n relationship.
  • Rails Mode ON

    We understood the meaning of databases, tried some basic queries, and made the relationship between tables. But how can we use that knowledge in the Ruby on Rails and web development World?

    First of all: Rails is Rails. The Database is Database. Is it obvious? But people usually get confused about that.

    A User model can represent a Users table. But the model isn’t the table.

  • In the database, we have tables and rows.
  • On rails, we have models (classes) and objects.
  • Imagine a blog site. The blog needs an author for each post. So we create an Authors table with some columns (first_name, last_name, etc)

    .. in the migration, we add columns first_name, last_name, email, birthday, email, created_at, and updated_at. (created_at and updated_at are created by the t.timestamps code.

    So we created a migration (Ruby code), run rake db:migrate command in the terminal and it generates a table Authors with first_name, last_name, email, birthday, email, created_at, and updated_at columns.

    Back to Rails, we can create an Author model:

    So now we have an Authors table with some columns and an Author model.

    Using Rails Console

    Open the terminal and type bundle exec rails c. Remember, we are in the RAILS console, so we have classes, objects, attributes, etc.

    Relationship on Rails

    We created an Authors table/model. What we need now is a Posts table/model. An author has many posts and a post belongs to a specific author. The relationship here is one to many (1-n). Remember?

    So when we create a Posts table, we need to store a reference to the post’s author (column author_id in the Posts table). It’s known as the Foreign Key.

    And how do we relate the models?

    author has_many posts post belongs_to an author Using Rails Console

    * Quick explanation about has_many and belongs_to. Both codes are methods defined on ActiveRecord class. If you see, we create our models inheriting from ActiveRecord::Base.

    Remember on Ruby Foundation that we studied about Object Oriented Programming, the Inheritance part? This is why we can use has_many and belongs_to methods without defining it anywhere on our application. Rails handles it for us.

    If you want to understand this concept deep, clone the Rails repo or understand the Behind the Scenes of the ‘Has Many’ Active Record Association.

    Queries on Rails

    We can query using ActiveRecord methods:

  • all: Get all objects from a specific model.
  • Behind the scenes, it is executing the SELECT * FROM posts query.

  • find: Using find we can get the object by the id (primary key).
  • Behind the scenes, it is executing SELECT * FROM posts WHERE id = 1 query.

  • where: Get the objects that pass the conditions.
  • Behind the scenes, it is executing SELECT * FROM posts WHERE title = 'Database & Rails'query.

  • order: Sort all objects based on a column.
  • Behind the scenes, it is executing SELECT * FROM posts ORDER BY created_at DESC query.

    That’s all!

    We learned a lot here. I hope you guys could appreciate the content and learn more about how the Databases and Rails models work.

    This is one more step forward in my journey to learning and mastering Rails and web development. You can see the documentation of my complete journey here on my Renaissance Developer publication.

    Have fun, keep learning and coding.


    Exam Ref 70-768 Developing SQL Data Models | killexams.com real questions and Pass4sure dumps

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    Building Enterprise Performance Into a Graph Database | killexams.com real questions and Pass4sure dumps

    This article is featured in the new DZone Guide to Databases: Relational and Beyond. Get your free copy for more insightful articles, industry statistics, and more!

    This article introduces some of the key concepts of graph databases and their use cases. It explains how a focus on speed and scalability allows a modern “second-generation” graph database to tackle enterprise-level use cases to enable delivery of high-performance machine learning.

    Introduction

    The NoSQL (“not only SQL”) space presents a number of different data models and database systems which can be more suitable than relational systems for particular types of data and use cases. Among these are graph databases, in which data is formed of a collection of nodes, the edges that connect them, and a set of properties. Nodes are entities, such as people or items, edges represent the relationships between the nodes, and properties are information about the nodes and edges.

    The underlying data model of common graph databases is either an RDF triple store or a labeled property graph, and you can find out more in an article here on DZone, which describes the differences between the two approaches. RDF databases and property graphs might be native products, but they can also be built on top of other database types, such as a NoSQL database like Hadoop or Cassandra.

    Image title

    A property graph, illustrating nodes, properties, and edges from Wikimedia Commons [CC0].

    Graph Database Use Case

    Interconnection is the key differentiator for graph databases. The edges represent relationships more directly than other database systems and can reveal patterns about the connections between data without the use of foreign keys or MapReduce.Graph databases are excellent for navigating a relationship structure quickly — for example, the number of steps needed to get from one node to another.

    Wherever you use a relational database, you can use a graph database; to get the most from it, you need to structure your data to take advantage of the relationships. Typical use cases include recommendation engines, fraud detection, rules engines, text processing and text analytics in media and publishing, and discovery projects that explore a “data lake” to uncover previously unseen relationships between entities — an approach which has applications in security and research. A great example is the recent use of a graph database by the International Consortium of Investigative Journalists (ICIJ). Their analysis of the “Panama Papers” revealed highly interconnected networks of offshore tax structures. This latter use case is sometimes referred to as cognitive computing since it uses data mining and pattern recognition.

    Graph databases areexcellent for navigatinga relationship structurequickly — for example, thenumber of steps needed toget from one node to another.

    In the current age of interconnected data, graph databases are showing increased uptake within large online systems and have become the fastest growing category of NoSQL databases. A recent report from IBM surveyed over 1,300 entrepreneurs and developers worldwide about their current and planned use for graph databases, and 43% of respondents were reported to be using or planning to use graph technology. New graph databases are emerging, and existing vendors are adding graph capabilities to their current solutions. Some of the key players include Neo4J, TitanDB, Blazegraph, HypergraphDB, OrientDB, IBM Graph, and Amazon’s Neptune.

    Historical Disadvantages of Graph Databases

    Neither graph computing as a field nor graph databases as a technology are particularly new; both have been around for at least 30 years. Given the exciting possibilities that they offer, you might wonder why they have not been more widely adopted before now. Early adopters of the first generation of graph databases have reported some issues, which include the following:

  • Some disk-based graph databases are unable to handle a constant stream of updates and stay sufficiently responsive to provide high performance on queries.

  • Not all traditional graph databases are suitable for transactions and some are more focused on providing analytical frameworks.

  • It is difficult to determine how to shard or partition data to get the best performance out of a graph database system as it scales.

  • It can be difficult to know how to model domain data onto a graph since it requires a specialist skill set — that is, proficiency in defining an ontology.

  • When the data model is defined, it is essential that data loaded into the graph database is consistent with that ontology. Graph databases, like other NoSQL databases, delegate adherence to a schema to the application system and do not enforce a schema, so the data entering the database needs guaranteed consistency up front.

  • Introducing Memgraph

    In the rest of this article, I am going to look at how the next generation of graph databases is tackling some of the drawbacks of the trailblazing, early graph database systems. I will use Memgraph as an example because I have access to the team for technical support, and I would also encourage you to reach out to them if you have questions. But, as ever, I should point out that other graph databases are available. Memgraph is a next-generation graph database system which sits in-memory and has been optimized for real-time transactional use cases, aiming to handle highly concurrent operational and analytical workloads within the enterprise space.

    The Memgraph architecture sets out to eliminate the issues leveled at earlier generation graph databases by prioritizing“four pillars:” speed, scale, simplicity, and security. Let’s look at the first two of these in some more detail.

    Speed

    Memgraph supports real-time use cases for enterprises with colossal amounts of data. The team has achieved high-performance benchmarks, demonstrating low latency and high throughput on high volumes of read and write queries (with ACID transactions) on real-world scale datasets. For reasons of space and timing, I can’t share the benchmark results here, but they will be published within the next few weeks, and I can say that they stack up well when compared against incumbent graph database systems.

    The Memgraph architecturesets out to eliminate the issuesleveled at earlier generationgraph databases by prioritizing“four pillars:” speed, scale,simplicity, and security.

    Memgraph is capable of loading tens of thousands of nodes/edges per second on a single machine. The database achieves high throughput by using highly concurrent (and sometimes seven lock-free) data structures and multi-version concurrency control (MVCC). This ensures that writes never block reads and vice versa. Traditional databases manage concurrency with global locks, which results in some processes blocking others until they complete and release the lock. Memgraph’s implementation of MVCC provides snapshot isolation level which allows better performance than serializability while avoiding most of the concurrency anomalies.

    Additionally, Memgraph uses a highly concurrent skip list for indexing purposes. Skip lists represent an efficient technique for searching and manipulating data, delivering concurrency and performance benefits beyond those seen for other graph databases and disk-based databases which use B-Trees to store indexes.

    Scale

    On a single machine, Memgraph scales up to the size of a main memory or disk space where properties could be stored on disk. In a distributed system, the graph is automatically repartitioned in the background to improve query execution time and scalability.

    Memgraph features a distributed query planning and execution engine. Each plan is divided into two; a plan that will be executed on the machine where the query is received and a plan that will be executed on the other machines. Nodes are allowed to exchange data during the execution process to maximize performance.

    In its distributed environment, Memgraph offers a custom and high-performance implementation of common graph algorithms such as level-synchronous parallel breadth-first search(BFS), which in many cases outperforms a single machine BFS.

    To improve query performance and scalability, Memgraph runs a dynamic graph partitioning algorithm in the background to minimize the number of crossing edges between machines whilst keeping the cluster optimally balanced.

    AI and Analytics

    Memgraph can integrate with the most popular machine learning tool such as TensorFlow and PyTorch, readily allowing the stored data to be used to train a model. To facilitate training and production deployment across the enterprise space, theMemgraph client will be wrapped in a TensorFlow operation to allow direct querying into Memgraph. A similar approach will be used for PyTorch and ONNX deep learning, with the goal of making the data within Memgraph easily accessible to data scientists — for example, those developing systems for fraud detection in finance and retail.

    Thanks to its in-memory architecture, Memgraph is also suitable for running analytical workloads. Algorithms like BFSand Weighted Shortest Path constitute the core of the query execution stack.

    Summary

    Graph databases are increasing in popularity, and though the next-generation graph technology is still very much under development, it promises to eliminate some of the current disadvantages and deliver a powerful backend for use in enterprise and beyond.

    If you have specific questions about Memgraph, you may find them answered by their FAQ, but you can find out more by contacting the team.

    This article is featured in the new DZone Guide to Databases: Relational and Beyond. Get your free copy for more insightful articles, industry statistics, and more!



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