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Category: arangodb

  • Khóa học miễn phí A Multi-Model First Database nhận dự án làm có lương

    ArangoDB – A Multi-Model First Database

    ArangoDB is hailed as a native multi-model database by its developers. This is unlike other NoSQL databases. In this database, the data can be stored as documents, key/value pairs or graphs. And with a single declarative query language, any or all of your data can be accessed. Moreover, different models can be combined in a single query. And, owing to its multi-model style, one can make lean applications, which will be scalable horizontally with any or all of the three data models.

    Layered vs. Native Multi-Model Databases

    In this section, we will highlight a crucial difference between native and layered multimodel databases.

    Many database vendors call their product “multi-model,” but adding a graph layer to a key/value or document store does not qualify as native multi-model.

    With ArangoDB, the same core with the same query language, one can club together different data models and features in a single query, as we have already stated in previous section. In ArangoDB, there is no “switching” between data models, and there is no shifting of data from A to B to execute queries. It leads to performance advantages to ArangoDB in comparison to the “layered” approaches.

    The Need for Multimodal Database

    Interpreting the [Fowler’s] basic idea leads us to realize the benefits of using a variety of appropriate data models for different parts of the persistence layer, the layer being part of the larger software architecture.

    According to this, one might, for example, use a relational database to persist structured, tabular data; a document store for unstructured, object-like data; a key/value store for a hash table; and a graph database for highly linked referential data.

    However, traditional implementation of this approach will lead one to use multiple databases in the same project. It can lead to some operational friction (more complicated deployment, more frequent upgrades) as well as data consistency and duplication issues.

    The next challenge after unifying the data for the three data models, is to devise and implement a common query language that can allow data administrators to express a variety of queries, such as document queries, key/value lookups, graphy queries, and arbitrary combinations of these.

    By graphy queries, we mean queries involving graph-theoretic considerations. In particular, these may involve the particular connectivity features coming from the edges. For example, ShortestPath, GraphTraversal, and Neighbors.

    Graphs are a perfect fit as data model for relations. In many real-world cases such as social network, recommendor system, etc., a very natural data model is a graph. It captures relations and can hold label information with each edge and with each vertex. Further, JSON documents are a natural fit to store this type of vertex and edge data.

    ArangoDB ─ Features

    There are various notable features of ArangoDB. We will highlight the prominent features below −

    • Multi-model Paradigm
    • ACID Properties
    • HTTP API

    ArangoDB supports all popular database models. Following are a few models supported by ArangoDB −

    • Document model
    • Key/Value model
    • Graph model

    A single query language is enough to retrieve data out of the database

    The four properties Atomicity, Consistency, Isolation, and Durability (ACID) describe the guarantees of database transactions. ArangoDB supports ACID-compliant transactions.

    ArangoDB allows clients, such as browsers, to interact with the database with HTTP API, the API being resource-oriented and extendable with JavaScript.


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  • Khóa học miễn phí Basic Concepts & Terminologies nhận dự án làm có lương

    Basic Concepts and Terminologies

    In this chapter, we will discuss the basic concepts and terminologies for ArangoDB. It is very important to have a knowhow of the underlying basic terminologies related to the technical topic we are dealing with.

    The terminologies for ArangoDB are listed below −

    • Document
    • Collection
    • Collection Identifier
    • Collection Name
    • Database
    • Database Name
    • Database Organization

    From the perspective of data model, ArangoDB may be considered a document-oriented database, as the notion of a document is the mathematical idea of the latter. Document-oriented databases are one of the main categories of NoSQL databases.

    The hierarchy goes like this: Documents are grouped into collections, and Collections exist inside databases

    It should be obvious that Identifier and Name are two attributes for the collection and database.

    Usually, two documents (vertices) stored in document collections are linked by a document (edge) stored in an edge collection. This is ArangoDB”s graph data model. It follows the mathematical concept of a directed, labeled graph, except that edges don”t just have labels, but are full-blown documents.

    Having become familiar with the core terms for this database, we begin to understand ArangoDB”s graph data model. In this model, there exist two types of collections: document collections and edge collections. Edge collections store documents and also include two special attributes: first is the _from attribute, and the second is the _to attribute. These attributes are used to create edges (relations) between documents essential for graph database. Document collections are also called vertex collections in the context of graphs (see any graph theory book).

    Let us now see how important databases are. They are important because collections exist inside databases. In one instance of ArangoDB, there can be one or many databases. Different databases are usually used for multi-tenant setups, as the different sets of data inside them (collections, documents, etc.) are isolated from one another. The default database _system is special, because it cannot be removed. Users are managed in this database, and their credentials are valid for all the databases of a server instance.


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  • Khóa học miễn phí ArangoDB – Home nhận dự án làm có lương

    ArangoDB tutorial

    ArangoDB Tutorial







    Apparently, the world is becoming more and more connected. And at some point in the very near future, your kitchen bar may well be able to recommend your favorite brands of whiskey! This recommended information may come from retailers, or equally likely it can be suggested from friends on Social Networks; whatever it is, you will be able to see the benefits of using graph databases, if you like the recommendations. This tutorial explains the various aspects of ArangoDB which is a major contender in the landscape of graph databases. Starting with the basics of ArangoDB which focuses on the installation and basic concepts of ArangoDB, it gradually moves on to advanced topics such as CRUD operations and AQL. The last few chapters in this tutorial will help you understand how to deploy ArangoDB as a single instance and/or using Docker.

    Audience

    This tutorial is meant for those who are interested in learning ArangoDB as a Multimodel Database. Graph databases are spreading like wildfire across the industry and are making an impact on the development of new generation applications. So anyone who is interested in learning different aspects of ArangoDB, should go through this tutorial.

    Prerequisites

    Before proceeding with this tutorial, you should have the basic knowledge of Database, SQL, Graph Theory, and JavaScript.

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  • Khóa học miễn phí Data Models & Modeling nhận dự án làm có lương

    ArangoDB – Data Models and Modeling

    In this chapter, we will focus on the following topics −

    • Database Interaction
    • Data Model
    • Data Retrieval

    ArangoDB supports document based data model as well as graph based data model. Let us first describe the document based data model.

    ArangoDB”s documents closely resemble the JSON format. Zero or more attributes are contained in a document, and a value attached with each attribute. A value is either of an atomic type, such as a number, Boolean or null, literal string, or of a compound data type, such as embedded document/object or an array. Arrays or sub-objects may consist of these data types, which implies that a single document can represent non-trivial data structures.

    Further in hierarchy, documents are arranged into collections, which may contain no documents (in theory) or more than one document. One can compare documents to rows and collections to tables (Here tables and rows refer to those of relational database management systems – RDBMS).

    But, in RDBMS, defining columns is a prerequisite to store records into a table, calling these definitions schemas. However, as a novel feature, ArangoDB is schema-less – there is no a priori reason to specify what attributes the document will have.

    And unlike RDBMS, each document can be structured in a completely different way from another document. These documents can be saved together in one single collection. Practically, common characteristics may exist among documents in the collection, however the database system, i.e., ArangoDB itself, does not bind you to a particular data structure.

    Now we will try to understand ArangoDB”s [graph data model], which requires two kinds of collections — the first is the document collections (known as vertices collections in group-theoretic language), the second is the edge collections. There is a subtle difference between these two types. Edge collections also store documents, but they are characterized by including two unique attributes, _from and _to for creating relations between documents. In practice, a document (read edge) links two documents (read vertices), both stored in their respective collections. This architecture is derived from the graph-theoretic concept of a labeled, directed graph, excluding edges that can have not only labels, but can be a complete JSON like document in itself.

    To compute fresh data, delete documents or to manipulate them, queries are used, which select or filter documents as per the given criteria. Either being simple as an “example query” or being as complex as “joins”, queries are coded in AQL – ArangoDB Query Language.


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  • Khóa học miễn phí ArangoDB – Web Interface nhận dự án làm có lương

    ArangoDB – Web Interface

    In this chapter, we will learn how to enable/disable the Authentication, and how to bind the ArangoDB to the Public Network Interface.

    # arangosh --server.endpoint tcp://127.0.0.1:8529 --server.database "_system"

    It will prompt you for the password saved earlier −

    Please specify a password:

    Use the password you created for root, at the configuration.

    You can also use curl to check that you are actually getting HTTP 401 (Unauthorized) server responses for requests that require authentication −

    # curl --dump - http://127.0.0.1:8529/_api/version

    Output

    HTTP/1.1 401 Unauthorized
X-Content-Type-Options: nosniff
Www-Authenticate: Bearer token_type = "JWT", realm = "ArangoDB"
Server: ArangoDB
Connection: Keep-Alive
Content-Type: text/plain; charset = utf-8
Content-Length: 0

    To avoid entering the password each time during our learning process, we will disable the authentication. For that, open the configuration file −

    # vim /etc/arangodb3/arangod.conf

    You should change the color scheme if the code is not properly visible.

    :colorscheme desert

    Set authentication to false as shown in the screenshot below.

    Output Window Root Password

    Restart the service −

    # service arangodb3 restart

    On making the authentication false, you will be able to login (either with root or created user like Harry in this case) without entering any password in please specify a password.

    Let us check the api version when the authentication is switched off −

    # curl --dump - http://127.0.0.1:8529/_api/version

    Output

    HTTP/1.1 200 OK
X-Content-Type-Options: nosniff
Server: ArangoDB
Connection: Keep-Alive
Content-Type: application/json; charset=utf-8
Content-Length: 60
{"server":"arango","version":"3.1.27","license":"community"}

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  • Khóa học miễn phí ArangoDB – Advantages nhận dự án làm có lương

    ArangoDB – Advantages

    Following are the advantages of using ArangoDB −

    Consolidation

    As a native multi-model database, ArangoDB eliminates the need to deploy multiple databases, and thus decreases the number of components and their maintenance. Consequently, it reduces the technology-stack complexity for the application. In addition to consolidating your overall technical needs, this simplification leads to lower total cost of ownership and increasing flexibility.

    Simplified Performance Scaling

    With applications growing over time, ArangoDB can tackle growing performance and storage needs, by independently scaling with different data models. As ArangoDB can scale both vertically and horizontally, so in case when your performance demands a decrease (a deliberate, desired slow-down), your back-end system can be easily scaled down to save on hardware as well as operational costs.

    Reduced Operational Complexity

    The decree of Polyglot Persistence is to employ the best tools for every job you undertake. Certain tasks need a document database, while others may need a graph database. As a result of working with single-model databases, it can lead to multiple operational challenges. Integrating single-model databases is a difficult job in itself. But the biggest challenge is building a large cohesive structure with data consistency and fault tolerance between separate, unrelated database systems. It may prove nearly impossible.

    Polyglot Persistence can be handled with a native multi-model database, as it allows to have polyglot data easily, but at the same time with data consistency on a fault tolerant system. With ArangoDB, we can use the correct data model for the complex job.

    Strong Data Consistency

    If one uses multiple single-model databases, data consistency can become an issue. These databases aren’t designed to communicate with each other, therefore some form of transaction functionality needs to be implemented to keep your data consistent between different models.

    Supporting ACID transactions, ArangoDB manages your different data models with a single back-end, providing strong consistency on a single instance, and atomic operations when operating in cluster mode.

    Fault Tolerance

    It is a challenge to build fault tolerant systems with many unrelated components. This challenge becomes more complex when working with clusters. Expertise is required to deploy and maintain such systems, using different technologies and/or technology stacks. Moreover, integrating multiple subsystems, designed to run independently, inflict large engineering and operational costs.

    As a consolidated technology stack, multi-model database presents an elegant solution. Designed to enable modern, modular architectures with different data models, ArangoDB works for cluster usage as well.

    Lower Total Cost of Ownership

    Each database technology requires ongoing maintenance, bug fixing patches, and other code changes which are provided by the vendor. Embracing a multi-model database significantly reduces the related maintenance costs simply by eliminating the number of database technologies in designing an application.

    Transactions

    Providing transactional guarantees throughout multiple machines is a real challenge, and few NoSQL databases give these guarantees. Being native multi-model, ArangoDB imposes transactions to guarantee data consistency.


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  • Khóa học miễn phí ArangoDB – Command Line nhận dự án làm có lương

    ArangoDB – Command Line

    In this chapter, we will discuss how Arangosh works as the Command Line for ArangoDB. We will start by learning how to add a Database user.

    Note − Remember numeric keypad might not work on Arangosh.

    Let us assume that the user is “harry” and password is “hpwdb”.

    127.0.0.1:8529@_system> require("org/arangodb/users").save("harry", "hpwdb");

    Output

    {
   "user" : "harry",
   "active" : true,
   "extra" : {},
   "changePassword" : false,
   "code" : 201
}

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  • Khóa học miễn phí ArangoDB – System Requirements nhận dự án làm có lương

    ArangoDB – System Requirements

    In this chapter, we will discuss the system requirements for ArangoDB.

    The system requirements for ArangoDB are as follows −

    • A VPS Server with Ubuntu Installation
    • RAM: 1 GB; CPU : 2.2 GHz

    For all the commands in this tutorial, we have used an instance of Ubuntu 16.04 (xenial) of RAM 1GB with one cpu having a processing power 2.2 GHz. And all the arangosh commands in this tutorial were tested for the ArangoDB version 3.1.27.

    How to Install ArangoDB?

    In this section, we will see how to install ArangoDB. ArangoDB comes pre-built for many operating systems and distributions. For more details, please refer to the ArangoDB documentation. As already mentioned, for this tutorial we will use Ubuntu 16.04×64.

    The first step is to download the public key for its repositories −

    # wget https://www.arangodb.com/repositories/arangodb31/
xUbuntu_16.04/Release.key

    Output

    --2017-09-03 12:13:24-- https://www.arangodb.com/repositories/arangodb31/xUbuntu_16.04/Release.key
Resolving 
(www.arangodb.com)... 104.25.1 64.21, 104.25.165.21,
2400:cb00:2048:1::6819:a415, ...
Connecting to 
(www.arangodb.com)|104.25. 164.21|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 3924 (3.8K) [application/pgpkeys]
Saving to: ‘Release.key’
Release.key 100%[===================>] 3.83K - .-KB/s in 0.001s
2017-09-03 12:13:25 (2.61 MB/s) - ‘Release.key’ saved [39 24/3924]

    The important point is that you should see the Release.key saved at the end of the output.

    Let us install the saved key using the following line of code −

    # sudo apt-key add Release.key

    Output

    OK

    Run the following commands to add the apt repository and update the index −

    # sudo apt-add-repository ''deb
https://www.arangodb.com/repositories/arangodb31/xUbuntu_16.04/ /''
# sudo apt-get update

    As a final step, we can install ArangoDB −

    # sudo apt-get install arangodb3

    Output

    Reading package lists... Done
Building dependency tree
Reading state information... Done
The following package was automatically installed and is no longer required:
grub-pc-bin
Use ''sudo apt autoremove'' to remove it.
The following NEW packages will be installed:
arangodb3
0 upgraded, 1 newly installed, 0 to remove and 17 not upgraded.
Need to get 55.6 MB of archives.
After this operation, 343 MB of additional disk space will be used.

    Press Enter. Now the process of installing ArangoDB will start −

    Get:1 
arangodb3 3.1.27 [55.6 MB]
Fetched 55.6 MB in 59s (942 kB/s)
Preconfiguring packages ...
Selecting previously unselected package arangodb3.
(Reading database ... 54209 files and directories currently installed.)
Preparing to unpack .../arangodb3_3.1.27_amd64.deb ...

Unpacking arangodb3 (3.1.27) ...
Processing triggers for systemd (229-4ubuntu19) ...
Processing triggers for ureadahead (0.100.0-19) ...
Processing triggers for man-db (2.7.5-1) ...
Setting up arangodb3 (3.1.27) ...
Database files are up-to-date.

    When the installation of ArangoDB is about to complete, the following screen appears −

    Installation of ArangoDB

    Here, you will be asked to provide a password for the ArangoDB root user. Note it down carefully.

    Select the yes option when the following dialog box appears −

    Configuration Dalog Box

    When you click Yes as in the above dialog box, the following dialog box appears. Click Yes here.

    Configuration Dalog Box 2

    You can also check the status of ArangoDB with the following command −

    # sudo systemctl status arangodb3

    Output

    arangodb3.service - LSB: arangodb
Loaded: loaded (/etc/init.d/arangodb3; bad; vendor pre set: enabled)
Active: active (running) since Mon 2017-09-04 05:42:35 UTC;
4min 46s ago
Docs: man:systemd-sysv-generator(8)
Process: 2642 ExecStart=/etc/init.d/arangodb3 start (code = exited,
status = 0/SUC
Tasks: 22
Memory: 158.6M
CPU: 3.117s
CGroup: /system.slice/arangodb3.service
├─2689 /usr/sbin/arangod --uid arangodb
--gid arangodb --pid-file /va
└─2690 /usr/sbin/arangod --uid arangodb
--gid arangodb --pid-file /va
Sep   04 05:42:33   ubuntu-512  systemd[1]:        Starting LSB:  arangodb...
Sep   04 05:42:33   ubuntu-512  arangodb3[2642]:  * Starting arango database server a
Sep   04 05:42:35   ubuntu-512  arangodb3[2642]:   {startup} starting up in daemon mode
Sep   04 05:42:35   ubuntu-512  arangodb3[2642]:   changed working directory for child
Sep   04 05:42:35   ubuntu-512  arangodb3[2642]:   ...done.
Sep   04 05:42:35   ubuntu-512  systemd[1]:        StartedLSB: arang odb.
Sep   04 05:46:59   ubuntu-512  systemd[1]:        Started LSB: arangodb. lines 1-19/19 (END)

    ArangoDB is now ready to be used.

    To invoke the arangosh terminal, type the following command in the terminal −

    # arangosh

    Output

    Please specify a password:

    Supply the root password created at the time of installation −

    _
__ _ _ __ __ _ _ __ __ _ ___ | |
/ | ''__/ _ | ’  / ` |/ _ / | ’
| (| | | | (| | | | | (| | () _  | | |
_,|| _,|| ||_, |_/|/| ||
|__/


    arangosh (ArangoDB 3.1.27 [linux] 64bit, using VPack 0.1.30, ICU 54.1, V8
5.0.71.39, OpenSSL 1.0.2g 1 Mar 2016)

Copyright (c) ArangoDB GmbH

Pretty printing values.
Connected to ArangoDB ''http+tcp://127.0.0.1:8529'' version: 3.1.27 [server],
database: ''_system'', username: ''root''

Please note that a new minor version ''3.2.2'' is available
Type ''tutorial'' for a tutorial or ''help'' to see common examples
127.0.0.1:8529@_system> exit

    Output Window Root Password

    To log out from ArangoDB, type the following command −

    127.0.0.1:8529@_system> exit

    Output

    Uf wiederluege! Na shledanou! Auf Wiedersehen! Bye Bye! Adiau! ¡Hasta luego!
Εις το επανιδείν!

להתראות ! Arrivederci! Tot ziens! Adjö! Au revoir! さようなら До свидания! Até
Breve! !خداحافظ

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