Dokumen tersebut membahas tentang basis data, sistem manajemen basis data (DBMS), perbedaan antara SQL dan NoSQL, serta penggunaan ORM dalam framework Laravel.
Sederhananya, cloud computing (komputasi awan) adalah metode penyampaian berbagai layanan melalui internet. Sumber daya yang dimaksud contohnya adalah aplikasi seperti penyimpanan data, server, database, jaringan, dan perangkat lunak.
Introducing NoSQL and MongoDB to complement Relational Databases (AMIS SIG 14...Lucas Jellema
This presentation gives an brief overview of the history of relational databases, ACID and SQL and presents some of the key strentgths and potential weaknesses. It introduces the rise of NoSQL - why it arose, what is entails, when to use it. The presentation focuses on MongoDB as prime example of NoSQL document store and it shows how to interact with MongoDB from JavaScript (NodeJS) and Java.
Tracxn Research - Finance & Accounting Landscape, February 2017Tracxn
This report provides an overview of investment trends in the finance and accounting software sector. It covers entrepreneur activity, funding trends by stage and year, notable investments, subsectors and companies. The scope includes equity and debt funding for companies offering solutions such as accounting suites, bookkeeping, invoicing, payroll, expense management, auditing, taxation and financial management software.
The document summarizes key trends from the 2015 Internet Trends report by Mary Meeker. It outlines that while global internet and smartphone user growth is still solid, the growth rate is slowing as adoption increases. It also notes that incremental users will be harder to obtain as adoption depends more on developing markets. Internet usage and engagement growth remains strong, especially for mobile video. Mobile advertising is growing faster than desktop but still lags in share of total internet advertising spending. The document also highlights new advertising formats and payment options optimized for mobile usage as well as the rise of vertical video viewing. Finally, it discusses how enterprise technology startups are reimagining business processes by addressing prior pain points in areas like communications, payments, analytics and
Tracxn Research - Construction Tech Landscape, February 2017Tracxn
The document provides an overview of investment trends in the construction technology sector from 2008 to 2016. It finds that the number of startups founded and funding rounds increased year over year, with total funding reaching $491 million in 2016. Early stage funding amounts and average ticket sizes also increased over time, with average early stage deals reaching $11.9 million in 2016. The report also analyzes subsectors of construction tech and provides examples of interesting startups.
Dokumen tersebut membahas tentang basis data, sistem manajemen basis data (DBMS), perbedaan antara SQL dan NoSQL, serta penggunaan ORM dalam framework Laravel.
Sederhananya, cloud computing (komputasi awan) adalah metode penyampaian berbagai layanan melalui internet. Sumber daya yang dimaksud contohnya adalah aplikasi seperti penyimpanan data, server, database, jaringan, dan perangkat lunak.
Introducing NoSQL and MongoDB to complement Relational Databases (AMIS SIG 14...Lucas Jellema
This presentation gives an brief overview of the history of relational databases, ACID and SQL and presents some of the key strentgths and potential weaknesses. It introduces the rise of NoSQL - why it arose, what is entails, when to use it. The presentation focuses on MongoDB as prime example of NoSQL document store and it shows how to interact with MongoDB from JavaScript (NodeJS) and Java.
Tracxn Research - Finance & Accounting Landscape, February 2017Tracxn
This report provides an overview of investment trends in the finance and accounting software sector. It covers entrepreneur activity, funding trends by stage and year, notable investments, subsectors and companies. The scope includes equity and debt funding for companies offering solutions such as accounting suites, bookkeeping, invoicing, payroll, expense management, auditing, taxation and financial management software.
The document summarizes key trends from the 2015 Internet Trends report by Mary Meeker. It outlines that while global internet and smartphone user growth is still solid, the growth rate is slowing as adoption increases. It also notes that incremental users will be harder to obtain as adoption depends more on developing markets. Internet usage and engagement growth remains strong, especially for mobile video. Mobile advertising is growing faster than desktop but still lags in share of total internet advertising spending. The document also highlights new advertising formats and payment options optimized for mobile usage as well as the rise of vertical video viewing. Finally, it discusses how enterprise technology startups are reimagining business processes by addressing prior pain points in areas like communications, payments, analytics and
Tracxn Research - Construction Tech Landscape, February 2017Tracxn
The document provides an overview of investment trends in the construction technology sector from 2008 to 2016. It finds that the number of startups founded and funding rounds increased year over year, with total funding reaching $491 million in 2016. Early stage funding amounts and average ticket sizes also increased over time, with average early stage deals reaching $11.9 million in 2016. The report also analyzes subsectors of construction tech and provides examples of interesting startups.
Cloud Spanner is the first and only relational database service that is both strongly consistent and horizontally scalable. With Cloud Spanner you enjoy all the traditional benefits of a relational database: ACID transactions, relational schemas (and schema changes without downtime), SQL queries, high performance, and high availability. But unlike any other relational database service, Cloud Spanner scales horizontally, to hundreds or thousands of servers, so it can handle the highest of transactional workloads.
Webinar - Bringing Game Changing Insights with Graph DatabasesDataStax
For many important problems, such as fraud detection, search, personalization, recommendation, and user authorization, data generated by graph databases are often easier and more efficient than other alternatives. Join our partner, Expero, to learn how applying user-centered strategies and leveraging the latest UI tools to your graph database can bring game-changing insights, finding critical concepts, clusters and relationships out of once-disconnected data.
View recording: https://youtu.be/sP2YpwmyHbg
Explore all current and on-demand DataStax webinars: http://www.datastax.com/resources/webinars
Dokumen tersebut membahas tentang database, termasuk pengertian database, jenis database, dan perbedaan antara database relasional dan non-relasional (NoSQL). Database dijelaskan sebagai kumpulan informasi yang disimpan secara sistematis untuk memperoleh informasi, sedangkan database relasional menyimpan data dalam bentuk tabel yang saling berhubungan dan NoSQL menyederhanakan proses database dengan menghilangkan redudansi data.
SQL Server on Linux will provide the SQL Server database engine running natively on Linux. It allows customers choice in deploying SQL Server on the platform of their choice, including Linux, Windows, and containers. The public preview of SQL Server on Linux is available now, with the general availability target for 2017. It brings the full power of SQL Server to Linux, including features like In-Memory OLTP, Always Encrypted, and PolyBase.
Tracxn Research - Insurance Tech Landscape, February 2017Tracxn
This document provides an overview of investment trends in the insurance technology sector from 2010 to 2016. It finds that the number of companies founded, funding rounds completed, and total funding amount have all increased significantly year-over-year in this period. The largest investments in the last year went to Oscar, Clover Health, Metromile, and Gusto. The report also analyzes trends by funding stage and subsectors within insurtech.
The document discusses the structure and components of HTML documents. It begins by explaining what HTML is and how it uses tags to provide formatting and semantic meaning. It then discusses the key elements of HTML documents, including the <html>, <head>, and <body> tags which form the basic skeleton of all HTML pages. The document also explains the differences between different types of tags and how HTML documents are interpreted by browsers.
2017 iosco research report on financial technologies (fintech)Ian Beckett
This document provides an overview of financial technologies (Fintech) and their intersection with securities markets regulation. It examines alternative financing platforms, retail trading/investment platforms, institutional trading platforms, and distributed ledger technologies. The report finds that Fintech is transforming traditional financial services through new business models and technologies. This raises regulatory questions around benefits/risks and implications for investor protection, market integrity, and stability. The document incorporates survey responses from global regulators on their experiences with Fintech.
Tracxn Research - Industrial Robotics Landscape, February 2017Tracxn
A number of investments in 2016 were made by CVCs such as GE Ventures, Caterpillar, Medtronic, and Mitsubishi UFJ Capital, who envision robotic technology to be implemented in their area of expertise.
David Yan offers an overview of Apache Apex, a stream processing engine used in production by several large companies for real-time data analytics.
Apache Apex uses a programming paradigm based on a directed acyclic graph (DAG). Each node in the DAG represents an operator, which can be data input, data output, or data transformation. Each directed edge in the DAG represents a stream, which is the flow of data from one operator to another.
As part of Apex, the Malhar library provides a suite of connector operators so that Apex applications can read from or write to various data sources. It also includes utility operators that are commonly used in streaming applications, such as parsers, deduplicators and join, and generic building blocks that facilitate scalable state management and checkpointing.
In addition to processing based on ingression time and processing time, Apex supports event-time windows and session windows. It also supports windowing, watermarks, allowed lateness, accumulation mode, triggering, and retraction detailed by Apache Beam as well as feedback loops in the DAG for iterative processing and at-least-once and “end-to-end” exactly-once processing guarantees. Apex provides various ways to fine-tune applications, such as operator partitioning, locality, and affinity.
Apex is integrated with several open source projects, including Apache Beam, Apache Samoa (distributed machine learning), and Apache Calcite (SQL-based application specification). Users can choose Apex as the backend engine when running their application model based on these projects.
David explains how to develop fault-tolerant streaming applications with low latency and high throughput using Apex, presenting the programming model with examples and demonstrating how custom business logic can be integrated using both the declarative high-level API and the compositional DAG-level API.
MongoDB NoSQL database a deep dive -MyWhitePaperRajesh Kumar
This document provides an overview of MongoDB, a popular NoSQL database. It discusses why NoSQL databases were created, the different types of NoSQL databases, and focuses on MongoDB. MongoDB is a document-oriented database that stores data in JSON-like documents with dynamic schemas. It provides horizontal scaling, high performance, and flexible data models. The presentation covers MongoDB concepts like databases, collections, documents, CRUD operations, indexing, sharding, replication, and use cases. It provides examples of modeling data in MongoDB and considerations for data and schema design.
This document discusses Kubernetes usage at VMware SAAS. It covers dynamic provisioning of applications on Kubernetes, monitoring tools used like DataDog and Log Insight, and best practices for upgrading Kubernetes clusters. Key points include using stateless applications where possible, service discovery using Kubernetes services, dynamic provisioning using an onboarding service, and performing rolling upgrades for stateful applications to minimize downtime.
This document summarizes a legal research paper about regulating corporate venture capital (CVC). It finds that CVC has grown dramatically since 2008 and now plays an important role in startup financing and the rise of "unicorns" (private companies valued over $1 billion). However, CVC faces little regulation. The paper aims to address this by analyzing the legal implications of CVC in two areas: securities regulation and conflicts of interest. It examines case studies of several prominent CVC firms like GV and Intel Capital to understand current disclosure practices and argues more transparency is needed given CVC's influence on private markets and company boards.
Big data is characterized by 3Vs - volume, velocity, and variety. Hadoop is a framework for distributed processing of large datasets across clusters of computers. It provides HDFS for storage, MapReduce for batch processing, and YARN for resource management. Additional tools like Spark, Mahout, and Zeppelin can be used for real-time processing, machine learning, and data visualization respectively on Hadoop. Benefits of Hadoop include ease of scaling to large data, high performance via parallel processing, reliability through data protection and failover.
Dokumen tersebut membahas tentang database, ORM, dan contoh penggunaan ORM di Laravel. Secara ringkas, dokumen menjelaskan pengertian database dan manfaatnya, perbedaan antara SQL dan NoSQL, pengertian ORM beserta manfaatnya, konsep Eloquent ORM di Laravel, dan contoh penggunaan ORM untuk menambahkan, mengupdate, dan menghapus data di Laravel.
Dokumen tersebut membahas tentang ORM (Object Relational Mapping) pada Laravel, yaitu teknik yang digunakan Laravel untuk mengkonversi data antara bahasa pemrograman berorientasi objek dengan database relasional, dengan contoh ORM yang digunakan Laravel.
Dokumen tersebut membahas tentang basis data, sistem manajemen basis data (DBMS), perbedaan antara SQL dan NoSQL, contoh aplikasi SQL dan NoSQL, Object Relational Mapping (ORM), dan Eloquent ORM framework di Laravel.
Cloud Spanner is the first and only relational database service that is both strongly consistent and horizontally scalable. With Cloud Spanner you enjoy all the traditional benefits of a relational database: ACID transactions, relational schemas (and schema changes without downtime), SQL queries, high performance, and high availability. But unlike any other relational database service, Cloud Spanner scales horizontally, to hundreds or thousands of servers, so it can handle the highest of transactional workloads.
Webinar - Bringing Game Changing Insights with Graph DatabasesDataStax
For many important problems, such as fraud detection, search, personalization, recommendation, and user authorization, data generated by graph databases are often easier and more efficient than other alternatives. Join our partner, Expero, to learn how applying user-centered strategies and leveraging the latest UI tools to your graph database can bring game-changing insights, finding critical concepts, clusters and relationships out of once-disconnected data.
View recording: https://youtu.be/sP2YpwmyHbg
Explore all current and on-demand DataStax webinars: http://www.datastax.com/resources/webinars
Dokumen tersebut membahas tentang database, termasuk pengertian database, jenis database, dan perbedaan antara database relasional dan non-relasional (NoSQL). Database dijelaskan sebagai kumpulan informasi yang disimpan secara sistematis untuk memperoleh informasi, sedangkan database relasional menyimpan data dalam bentuk tabel yang saling berhubungan dan NoSQL menyederhanakan proses database dengan menghilangkan redudansi data.
SQL Server on Linux will provide the SQL Server database engine running natively on Linux. It allows customers choice in deploying SQL Server on the platform of their choice, including Linux, Windows, and containers. The public preview of SQL Server on Linux is available now, with the general availability target for 2017. It brings the full power of SQL Server to Linux, including features like In-Memory OLTP, Always Encrypted, and PolyBase.
Tracxn Research - Insurance Tech Landscape, February 2017Tracxn
This document provides an overview of investment trends in the insurance technology sector from 2010 to 2016. It finds that the number of companies founded, funding rounds completed, and total funding amount have all increased significantly year-over-year in this period. The largest investments in the last year went to Oscar, Clover Health, Metromile, and Gusto. The report also analyzes trends by funding stage and subsectors within insurtech.
The document discusses the structure and components of HTML documents. It begins by explaining what HTML is and how it uses tags to provide formatting and semantic meaning. It then discusses the key elements of HTML documents, including the <html>, <head>, and <body> tags which form the basic skeleton of all HTML pages. The document also explains the differences between different types of tags and how HTML documents are interpreted by browsers.
2017 iosco research report on financial technologies (fintech)Ian Beckett
This document provides an overview of financial technologies (Fintech) and their intersection with securities markets regulation. It examines alternative financing platforms, retail trading/investment platforms, institutional trading platforms, and distributed ledger technologies. The report finds that Fintech is transforming traditional financial services through new business models and technologies. This raises regulatory questions around benefits/risks and implications for investor protection, market integrity, and stability. The document incorporates survey responses from global regulators on their experiences with Fintech.
Tracxn Research - Industrial Robotics Landscape, February 2017Tracxn
A number of investments in 2016 were made by CVCs such as GE Ventures, Caterpillar, Medtronic, and Mitsubishi UFJ Capital, who envision robotic technology to be implemented in their area of expertise.
David Yan offers an overview of Apache Apex, a stream processing engine used in production by several large companies for real-time data analytics.
Apache Apex uses a programming paradigm based on a directed acyclic graph (DAG). Each node in the DAG represents an operator, which can be data input, data output, or data transformation. Each directed edge in the DAG represents a stream, which is the flow of data from one operator to another.
As part of Apex, the Malhar library provides a suite of connector operators so that Apex applications can read from or write to various data sources. It also includes utility operators that are commonly used in streaming applications, such as parsers, deduplicators and join, and generic building blocks that facilitate scalable state management and checkpointing.
In addition to processing based on ingression time and processing time, Apex supports event-time windows and session windows. It also supports windowing, watermarks, allowed lateness, accumulation mode, triggering, and retraction detailed by Apache Beam as well as feedback loops in the DAG for iterative processing and at-least-once and “end-to-end” exactly-once processing guarantees. Apex provides various ways to fine-tune applications, such as operator partitioning, locality, and affinity.
Apex is integrated with several open source projects, including Apache Beam, Apache Samoa (distributed machine learning), and Apache Calcite (SQL-based application specification). Users can choose Apex as the backend engine when running their application model based on these projects.
David explains how to develop fault-tolerant streaming applications with low latency and high throughput using Apex, presenting the programming model with examples and demonstrating how custom business logic can be integrated using both the declarative high-level API and the compositional DAG-level API.
MongoDB NoSQL database a deep dive -MyWhitePaperRajesh Kumar
This document provides an overview of MongoDB, a popular NoSQL database. It discusses why NoSQL databases were created, the different types of NoSQL databases, and focuses on MongoDB. MongoDB is a document-oriented database that stores data in JSON-like documents with dynamic schemas. It provides horizontal scaling, high performance, and flexible data models. The presentation covers MongoDB concepts like databases, collections, documents, CRUD operations, indexing, sharding, replication, and use cases. It provides examples of modeling data in MongoDB and considerations for data and schema design.
This document discusses Kubernetes usage at VMware SAAS. It covers dynamic provisioning of applications on Kubernetes, monitoring tools used like DataDog and Log Insight, and best practices for upgrading Kubernetes clusters. Key points include using stateless applications where possible, service discovery using Kubernetes services, dynamic provisioning using an onboarding service, and performing rolling upgrades for stateful applications to minimize downtime.
This document summarizes a legal research paper about regulating corporate venture capital (CVC). It finds that CVC has grown dramatically since 2008 and now plays an important role in startup financing and the rise of "unicorns" (private companies valued over $1 billion). However, CVC faces little regulation. The paper aims to address this by analyzing the legal implications of CVC in two areas: securities regulation and conflicts of interest. It examines case studies of several prominent CVC firms like GV and Intel Capital to understand current disclosure practices and argues more transparency is needed given CVC's influence on private markets and company boards.
Big data is characterized by 3Vs - volume, velocity, and variety. Hadoop is a framework for distributed processing of large datasets across clusters of computers. It provides HDFS for storage, MapReduce for batch processing, and YARN for resource management. Additional tools like Spark, Mahout, and Zeppelin can be used for real-time processing, machine learning, and data visualization respectively on Hadoop. Benefits of Hadoop include ease of scaling to large data, high performance via parallel processing, reliability through data protection and failover.
Dokumen tersebut membahas tentang database, ORM, dan contoh penggunaan ORM di Laravel. Secara ringkas, dokumen menjelaskan pengertian database dan manfaatnya, perbedaan antara SQL dan NoSQL, pengertian ORM beserta manfaatnya, konsep Eloquent ORM di Laravel, dan contoh penggunaan ORM untuk menambahkan, mengupdate, dan menghapus data di Laravel.
Dokumen tersebut membahas tentang ORM (Object Relational Mapping) pada Laravel, yaitu teknik yang digunakan Laravel untuk mengkonversi data antara bahasa pemrograman berorientasi objek dengan database relasional, dengan contoh ORM yang digunakan Laravel.
Dokumen tersebut membahas tentang basis data, sistem manajemen basis data (DBMS), perbedaan antara SQL dan NoSQL, contoh aplikasi SQL dan NoSQL, Object Relational Mapping (ORM), dan Eloquent ORM framework di Laravel.
Dokumen tersebut membahas tentang database, termasuk pengertian database, jenis-jenis database seperti database relasional dan non-relasional (NoSQL), serta contoh-contoh sistem manajemen database relasional dan non-relasional."
Ringkasan dokumen tersebut adalah:
(1) Dokumen tersebut membahas tentang pengertian Oracle sebagai sistem manajemen basis data relasional dan persaingannya dengan produk lain; (2) Dibahas pula kelebihan dan kekurangan Oracle dalam memenuhi kebutuhan organisasi besar; (3) Sejarah singkat pendirian perusahaan Oracle dan pengembangan produknya.
Dokumen tersebut membahas tentang database, perbedaan relational dan non-relational database beserta contohnya, konsep ORM pada database, dan dukungan framework Laravel terhadap ORM.
Dokumen tersebut membahas tentang sistem manajemen basis data dan komponennya secara singkat, termasuk DBMS, arsitektur database, bahasa database, model basis data, data warehouse, OLAP, data mining, dan sistem basis data terdistribusi.
Dokumen tersebut membahas tentang database relasional dan manajemen sistem basis data. Secara ringkas, database relasional menyimpan data dalam bentuk tabel-tabel yang saling berhubungan, sedangkan sistem manajemen basis data (DBMS) digunakan untuk mengelola database tersebut dan menjalankan operasi-operasi data.
Dokumen tersebut membahas tentang database Oracle yang terdistribusi. Teknologi ini memungkinkan akses data dari database lokal maupun jauh secara transparan, baik dalam lingkungan homogen maupun heterogen. Oracle mendukung replikasi dan fragmentasi data untuk meningkatkan ketersediaan, skalabilitas, dan kinerja akses data secara terdistribusi.
tugas mata kuliah sistem teknologi informasi,,,tentang basis data Julmianti
Dokumen tersebut membahas tentang basis data dan beberapa konsep dasarnya seperti definisi basis data, jenis-jenis basis data, karakteristik basis data, bahasa yang digunakan pada basis data, serta proteksi data.
1. TUGAS 4
Nama : NASRUL AKBAR ADIPANGGA
Nim : 1412510552
Tugas : Rekayasa Web
2. Basis data (database) adalah kumpulan data yang disimpan
secara sistematis di dalam komputer yang dapat diolah atau
dimanipulasi menggunakan perangkat lunak (program aplikasi) untuk
menghasilkan informasi. Pendefinisian basis data meliputi spesifikasi
berupa tipe data, struktur data dan juga batasan-batasan pada data
yang akan disimpan. Basis data merupakan aspek yang sangat
penting dalam sistem informasi karena berfungsi sebagai gudang
penyimpanan data yang akan diolah lebih lanjut. Basis data menjadi
penting karena dapat mengorganisasi data, menghidari duplikasi
data, menghindari hubungan antar data yang tidak jelas dan juga
update yang rumit.
Proses memasukkan dan mengambil data ke dan dari media
penyimpanan data memerlukan perangkat lunak yang disebut dengan
sistem manajemen basis data (database management system | DBMS).
DBMS merupakan sistem perangkat lunak yang memungkinkan
pengguna basis data (database user) untuk memelihara, mengontrol
dan mengakses data secara praktis dan efisien. Dengan kata lain,
semua akses ke basis data akan ditangani oleh DBMS. DBMS ini
3. Ada beberapa fungsi yang harus ditangani DBMS
seperti mengolah pendefinisian data, menangani
permintaan pengguna untuk mengakses data, memeriksa
sekuriti dan integriti data yang didefinisikan oleh DBA
(Database Administrator), menangani kegagalan dalam
pengaksesan data yang disebabkan oleh kerusakan sistem
maupun media penyimpanan (disk) dan juga menangani
unjuk kerja semua fungsi secara efisien. Tujuan utama
DBMS adalah untuk memberikan tinjauan abstrak data
kepada pengguna. Jadi sistem menyembunyikan informasi
tentang bagaimana data disimpan, dipelihara dan juga bisa
diakses secara efisien. Pertimbangan efisien di sini adalah
rancangan struktur data yang kompleks tetapi masih bisa
digunakan oleh pengguna awam tanpa mengetahui
kompleksitas strukturnya.
4. Mysql merupakan aplikasi pengolah database yang
bersifat open source, dikembangkan oleh Oracle
(sebelumnya Sun dan MySQL AB). MySQL adalah sebuah
perangkat lunak sistem manajemen basis data SQL .
NoSql merupakan sistem manajemen basis data yang di
identifikasikan dengan tidak mematuhi aturan pada model
sistem manajemen basis data.
NOSQL adalah database generasi terbaru yang
mengarahkan kepada database yang tidak berelasi (non-
relational), dapat disebarkan kepada siapapun (open-
source) dan berskala horisontal (horizontal scale).
Contoh aplikasi pada Sql adalah
Oracle, MS-SQL, Sqlite, dan Postgres .
Sedangkan pada NoSQL adalah MongoDB, HBase, Redis,
Bigtable, RavenDb, CouchDB, Cassandra, dan Neo4j.
5. Perbedaan SQL dan NoSQL terletak pada cara penulisan database.SQL
menggunakan relasional sebagai penyambung antara data-data di dalam
tabel database. Sedangkan NoSQL tidak menggunakan Relasional sebagai
cara mereka untuk menyambungkan antar data .
NoSQL tidak menggunakan Schema relational, Pada SQL user harus
mendefinisikan table yang akan digunakan. Pada NoSQL tidak perlu untuk
mendefinisikan terlebih dahulu Table yang akan digunakan.
Dalam Database SQL data berbentuk tabel yang terdiri dari sejumlah
baris,Sedangkan Pada NoSQL data tidak memiliki definisi skema standar
yang harus dipatuhi. NoSQL memiliki skema yang dinamis sedangkan
pada database SQL mengikuti skema yang telah ditetapkan.
Database NoSQL merupakan horizontal terukur sedangkan pada SQL
Database vertikal terukur.
Untuk memperbesar pada skala NoSQL hanya perlu tambahkan server DB
di cluster untuk load balancing.
Sedangkan pada SQL Untuk memperbesar skala harus menambahkan
tenaga dari perangkat CPU,SSD,RAM dan perangkat keras lainnya pada
server.
Pada database SQL penekanan pada sifat Atomicity, Consistency, Isolation
and Durability (ACID) sifat. Sedangkan pad NoSQL mengikuti teorema
Consistency, Availability and Partition (CAP) Brewers.
6. ORM (Object Relational Mapping) [Wiki] adalah suatu metode/teknik
pemrograman yang digunakan untuk mengkonversi data dari
lingkungan bahasa pemrograman berorientasi objek (OOP) dengan
lingkungan database relasional. Seperti kita ketahui, dalam aplikasi
enterprise kedua lingkungan tersebut berada pada sistem yang
berbeda, yaitu OOP berada pada sisi pemrograman aplikasi,
sedangkan database relasional berada pada sisi sistem database. Misi
utama dari ORM ini adalah menjembatani kedua sistem yang berbeda
tersebut.
ORM memiliki kemampuan untuk menciptakan objek database virtual,
yaitu suatu model database yang di representasikan kedalam sebuah
objek pada bahasa pemrograman OOP. Berikut ini adalah beberapa
kelebihan yang dimiliki ORM, yaitu:
Mempercepat pengembangan program. Contohnya, mengurangi
perulangan kode query, memudahkan pemakaian karena tabel-tabel
ter-representasikan dalam bentuk objek
Membuat akses data menjadi lebih abstrak dan portable. Hal ini
dikarenakan ORM menghandle pen-generate-an syntax SQL
berdasarkan vendor database-nya.
Mensupport pengkapsulan business rule pada lapisan Data Access.
Mengenerate boilerplate code (unit kode yang reusable) untuk fungsi
7. laravel pada dasarnya mendukung konsep OOP, maka bukan hal yang
mustahil bila kita juga memanfaatkan konsep ORM ini pada framework
Laravel. Di laravel kita akan mengenal yang namanya Eloquent. Eloquent
merupakan sebuah ORM yang dapat dikatakan sangat membantu sekali
bagi web developer pengguna laravel.
Pada laravel, setiap model hasil turunan dari Eloquent akan mewakili
sebuah table pada database. Tapi anda perlu memperhatikan 1 hal
yakni, meskipun sebuah model mewakili sebuah tabal, namun dalam
pratiknya terkadang kita seringkali menggunakan beberapa model untuk
mengambil data dari database. Kita bisa memanfaatkan relationship
pada database untuk mengambil data dari banyak tabel sekaligus.
Jadi kesimpulannya adalah kita dapat memanfaatkan fitur-fitur yang
sudah disediakan oleh laravel untuk melakukan query ke database
dengan memanfaatkan konsep ORM itu tadi, sehingga akan terasa lebih
fleksibel. Selain itu kita juga lebih gampang dalam memahaminya dan
kode programpun akan tampak lebih terorganisir