Categories
Articles

Malaysia on the fast lane to become Cloud Computing Hub – Malaysia Cloud & Datacenter Digital Summit 2020

Malaysia Cloud & Datacenter Digital Summit, organized by W.Media, took place virtually on October 8, 2020.

The digital event saw the coming together of more than 200 IT (Information Technology) and DC (Datacenter) professionals, business leaders, and other technology enthusiasts who discussed the future of the cloud, datacenter, 5G, IoT (Internet of things) in South East Asia, particularly Malaysia.

Cloud and datacenter were at the center of discussion and were closely knitted in almost all panel discussions and thought leadership presentations.

Let’s look at some of the key highlights of the digital event.

Malaysia Cloud & Datacenter Digital Summit 2020 – the major highlights

As mentioned in the starting of this write-up, cloud and datacenter technologies were one of the hot topics of discussion at the event.

Let’s explore the reason why.

Malaysia stands at the very edge of transforming into a full-fledged cloud computing hub and many factors or driving forces are leading towards this mega shift. In the budget 2020, the Malaysian government earmarked a whopping amount of MYR 21.6 bn into the National Fiberisation and Connectivity Plan (NFCP). This move indicates the government’s focus on accelerating digital transformation by promoting more cloud adoption and roll-out of 5G connectivity through Malaysia.

The event included key sessions by leading cloud and datacenter professionals who shared their views on the digital future of Malaysia and the growth drivers.

Let’s look at some of the key session highlights.

Role of Enterprise Architecture (EA) in driving digital transformation across organizations

In his opening presentation, Aaron Tan DaniChairman, IASA ASIA PACIFIC, shared how a well-defined EA blueprint can help organizations successfully implement their digital transformation goals. Quoting a prediction by Gartner, “By 2025, organizations will predominantly focus EA on delivering business outcomes from the perspectives of their business ecosystem” he said digital transformation has become the need of the hour. According to him, 2025 is this year- 2020 only, due to the COVID-19 induced push for getting digitally transformed.

Source: Malaysia Cloud and Datacenter Digital Summit, 2020

He further shared key designs of EA principles that can drive digital transformation across organizations, as well as the key challenges faced by enterprises when moving from computerization to digitalization.

Importance of cybersecurity and risk assessment during cloud migration

Highlighting the key cloud migration challenges and risk assessment, Sina Manavi – Group AIA, shared how cloud migration is not as easy as it sounds. Presence of multiple vendors, agents, servers, administration overheads, integration issues, etc. make the process a bit complex for the first-time movers. He shared a few cloud migration challenges faced by almost every organization willing to step into the cloud:

  • What security controls to use?
  • Building a cloud security framework
  • Building a data protection framework
  • Planning for legacy apps, asset inventory, etc.
  • Access to automation tools and integration capabilities

He further shared a few solutions to overcome the above challenges. According to him, setting up a cloud risk management and governance framework can simplify the cloud migration. He also emphasised the role of cloud service providers in helping organizations swiftly move towards the cloud.

Source: Malaysia Cloud and Datacenter Digital Summit, 2020

Lack of knowledge and cloud data management – key challenges to cloud adoption in Malaysia

In his session, Malaysia Cloud-First Strategy, IR. Wan Murdani Mohamad, shared Malaysia’s direction in accelerating cloud adoption from 2017 to 2021. The Malaysian government has set a target of achieving 50% cloud adoption by the year 2024. The focus in 2021 would be on the implementation of cloud-first strategy in the public sector.

To accelerate cloud adoption, Malaysia is focusing on two high impact domains – Governance and People. Formation of cloud computing committees and upskilling competencies across people through cloud awareness program are key strategies to speed-up the cloud adoption across the Malaysian economy.

He further stated lack of knowledge, skills, and experience in the cloud followed by cloud data management complexities as the key challenges that can hinder cloud adoption.

Digital Infra and cloud – the key drivers of datacenter growth in Malaysia

In his thought leadership presentation, Sabarinathan Sampath – SVP & COO, ZNet Technologies, shared his outlook on the datacenter growth in South East Asia, specifically Malaysia, and how cloud and digital infrastructure plays a key role in driving this growth.

Source: Malaysia Cloud and Datacenter Digital Summit, 2020

The presence of digital infra components like 5G, automation tools, cloud computing, and APIs can make businesses agile and help them in providing great user experience and build long-lasting customer relationships.

With its proactive measures to drive cloud adoption – from improvements in connectivity, energy sustainability, and business sophistication to enabling MYR 16 billion revenue opportunity for service providers with the advent of 5G, Malaysia is on a fast lane to cloud adoption.

Apart from key sessions and presentations, the event also had interviews of Wan Murdani Mohamad, MDEC, Vidit Arora, Securonix and interactive panel discussions like:

  • Next-gen Cybersecurity – How can Malaysia do better?

The participants were Alvin Teoh, MDEC; Peter Leong, Technology Program Director; Vidit Arora, Securonix; and Moderator: Fong Choong Fook, LGMS

  • Data Centers at the Crossroads: Transformational Strategies

The participants were Ong Chin Seong, PIKOM; Tan Tze Meng, MDEC; Mohamad Rejab bin Sulaiman, TM One; Rhys Cole, Powershield; and Moderator: James Rix, Arcadis UK

The event was sponsored by MDEC, Open Computing Singapore, HR.Exchange, Securonix, Insyghts Security, etc. DHN was one of the media partners.

Overall, it was an insightful event with a lot of takeaways for those in the cloud, datacenter, and technology domains.

If you missed the live event, you can watch the on-demand session to know more about the topics that were discussed.

If you’re looking to attend more such cloud and datacenter focused events, get ready to join Thailand Cloud and Datacenter Digital Summit on 4th November 2020. Register for this upcoming cloud event through this special link.

Categories
Articles

NoSQL Database Comparison – Alibaba Cloud, AWS, Google Cloud, IBM and Microsoft

Data is everywhere around us and we interact with it regularly. Whether you’re checking out the latest model of a smartphone or buying groceries online, you are interacting with data in one way or the other. We have been dealing with data for ages, what has changed now is the scale of data produced and the speed at which it is accessed.

Thanks to digital technologies like cloud, IoT (Internet of things), AI (Artificial Intelligence), machine learning, and more, companies are producing data at an exponential rate. This amount of data collected around the globe is too hefty to process.

According to a report, “People are generating 2.5 quintillion bytes of data each day.”

Here, traditional relational databases like SQL might not offer the required scalability and performance to process large amounts of data. Though relational databases are still relevant, alternative databases like NoSQL come with their own sets of advantages.

This article will help you understand:

.What is NoSQL database?

NoSQL stands for ‘not only SQL’. Big infrastructure providers like Google, Amazon, and Facebook recognized the scalability issue of SQL databases and hence introduced their alternative solutions like Bigtable, DynamoDB, and Cassandra, respectively to meet the changing demands.

NoSQL is an approach to database design. It can accommodate a wide variety of data models. Some of these include key-value, columnar, document, and graph formats. It offers improved scalability, performance, reliability, and consistency as compared to schema-based traditional relational databases.

The NoSQL databases are purpose-built to work with large sets of distributed data. They mostly refer to the databases built in the early 2000s for large-scale clustering of data produced by cloud and web applications.

The need for performance and scalability in cloud-based web applications outweighs the rigid data consistency that traditional relational database management systems provide.

NoSQL database is a form of unstructured storage. They do not have any fixed table structure – one important trait that differentiates them with the common relational databases.

  • NoSQL databases have a flexible schema. There can be different rows having different attributes or structure.
  • They work on a BASE model – Basically Available, Soft state, Eventual consistency.
  • In NoSQL, queries may not always see the latest data. Thus, consistency is guaranteed after some period.

.The advantages of NoSQL databases

  • NoSQL databases have a simpler structure without a schema and are flexible.
  • They are based on key-value points. This means that records are stored and retrieved using a key that is unique to every set of record.
  • NoSQL database can also have column store, key-value graph, document store, object store and other popular data store modes. Thus, they are multi-purpose as well.
  • Open-source NoSQL databases don’t require any expensive licensing fees.
  • They are easily scalable whether you are using an open-source or a proprietary solution. This is because the NoSQL databases can scale horizontally to distribute the load on all nodes. In SQL, this is done by replacing the main host with a higher capacity one, i.e. via vertical scaling.

Now when you know what NoSQL is and what are its advantages, it is time to look at some of the top NoSQL database solutions offered by leading service providers like AWS, Google Cloud, IBM, Alibaba Cloud, and Microsoft. We will also be taking a look at a NoSQL database comparison table for understanding the key differences.

.Comparison between NoSQL database solutions

1. Alibaba Cloud Tablestore

Tablestore is a fully managed NoSQL cloud database service offered by Alibaba Cloud. It can store a large amount of structured and semi-structured data using a variety of data models. Users can use Tablestore database to query and analyse data. Users can also migrate heterogeneous data to this database without any interruptions. With elastic resources and pay-as-you-go billing, it is an efficient and low-cost database management system. It offers high-consistency and service availability with globally spread data centres. Furthermore, distributed architecture and single table auto-scaling makes it highly elastic.

  • It is a fully managed database service. Users can simply focus on business research and development activities instead of worrying about hardware and software presetting, faults, configurations, security, etc.
  • With in-built shards and load balancing, Tablestore can automatically adjust the size of partitions, allowing users to store more data.
  • It creates multiple backups of data and stores them in different server racks.
  • It also offers consistency across three backups. The application can quickly read the data.
Source: Alibaba Cloud
2. Amazon DynamoDB

Amazon DynamoDB is a fast and flexible NoSQL database service that can deliver single-digit millisecond performance at any scale. It is a key-value and document database that is multi-region, fully managed, and durable.

The multi-master database is backed with in-built security, backup, restore, and in-memory caching for internet-scale applications.

  • DynamoDB is built to support the world’s largest-scale applications.
  • Users can build applications with unlimited throughput and storage.
  • The data stored in the database is replicated across multiple AWS regions. This allows local access to data for globally distributed applications.
  • Another great advantage of DynamoDB is that it is serverless. Users have no servers to manage or provision.
  • The database is designed to scale automatically up and down as per the system and capacity requirement.
  • It also supports ACID (Atomicity, Consistency, Isolation, and Durability) transactions – making it an enterprise-ready database.
Reference Architecture of a Weather Application, Source: Amazon Web Services
3. Azure Cosmos DB

Azure CosmosDB is a NoSQL database service by Microsoft that is globally distributed and multi-model. It allows users elastically and independently scales workloads with a click of a button.

Users can also take advantage of fast, single-digit-millisecond data access with the help of APIs like Cassandra, SQL, MongoDB, Gremlin or Tables. It provides comprehensive service level agreements (SLAs) for latency, throughput, availability, and consistency guarantees.

  • With globally spread Azure regions, users can build highly responsive and highly available applications worldwide.
  • It provides 99.999% availability for both write and read actions. It is deeply integrated with Azure Infrastructure and Transparent Multi-Master replication.
  • It offers unprecedented elastic scalability through transparent horizontal partitioning and multi-master replication.
  • Users do not need to deal with index or schema management as the database engine is fully-schema-agnostic.
Source: Microsoft
4. Google Cloud Bigtable

Cloud Bigtable is the fully managed and scalable NoSQL service by Google Cloud. It is best suited for large analytical and operational workloads. It allows users to store terabytes or even petabytes of data. It is ideal for storing large amounts of single-keyed data with very low latency. Cloud Bigtable stores data in scalable tables. These tables are composed of rows and columns. Each of the rows describes a single entity and are indexed by a single row key.

Data stored inside the Cloud Bigtable database is completely secure. The access to the data is controlled by Google Cloud project and the Identity and Access Management (IAM) roles. It also allows users to save a copy of schemas and data as backups.

  • Cloud Bigtable database is designed to scale in direct proportion to the number of machines in a cluster.
  • It can handle upgrades and restart automatically.
  • Users can also increase the size of a Cloud Bigtable cluster for a few hours to manage any large loads.

It is ideal for time-series data, marketing data, financial data, internet of things’ data, and graph data.

IoT use case reference architecture, Source: Google Cloud
5. IBM Cloudant

IBM Cloudant is a fully managed database service designed for hybrid multi-cloud applications. It is built on open-source Apache CouchDB and has a fully compatible API that allows data syncing to any cloud or the edge.

It is a distributed database service that can handle heavy workloads of large, fast-growing web and mobile apps. It is available as an SLA-backed and fully managed IBM Cloud service. Users can also download the service for on-premises installation.

  • It allows users to instantly deploy an instance, create a database, and independently scale.
  • It is ISO 27001, SOC 2 Type 2 compliant and HIPAA ready.
  • With 55+ data centres across the world and globally spread IBM Cloud regions, users can seamlessly distribute data across zones, regions, and cloud providers.
  • The service is compatible with Apache CouchDB, enabling users to access a wide variety of language libraries and rapidly build new applications. Thus, the service boasts of zero vendor lock-in.
AI use case, Source: IBM

Note: The services mentioned above in the NoSQL database comparison have been listed in alphabetical order.

.Tabular Comparison

NoSQL Database Comparison: DynamoDB Vs Bigtable Vs Cloudant Vs Tablestore Vs Azure CosmosDB

Comparison Points DynamoDB Cloud BigTable Cloudant Tablestore Azure CosmosDB
Developed By Amazon Web Services (AWS) Google IBM Alibaba Cloud Microsoft
Primary Database Model
  • Document Store
  • Key-Value store
Wide Column store Document Store Wide Column Store
  • Document store
  • Graph Store
  • Key-Value Store
  • Wide Column Store
Initial Release 2012 2015 2010 2016 2017
 

License

 

 

Commercial Commercial Commercial Commercial Commercial
Cloud-based Yes Yes Yes Yes Yes
Data Schema Schema-free Schema-free Schema-free Schema-free Schema-free
Server OS Hosted Hosted Hosted Hosted Hosted
Supported Programming Languages*
  • NET
  • Ruby
  • Erlang
  • ColdFusion
  • Groovy
  • Java
  • JavaScript
  • PHP
  • Perl
  • Python
  • C#
  • Go
  • C++
  • Java
  • JavaScript (Node.js)
  • Python
  • C#
  • Java
  • JavaScript
  • Objective-C
  • Ruby
  • PHP
  • Java
  • Python
  • .Net
  • C#
  • Java
  • JavaScript (Node.js)
  • Python
  • MongoDB Client drivers
Consistency
  • Eventual Consistency
  • Immediate Consistency
  • Immediate Consistency (for single clusters)
  • Eventual Consistency (for two or more replicate clusters)
Eventual Consistency Immediate Consistency
  • Bounded Staleness
  • Consistent Prefix
  • Eventual Consistency
  • Immediate Consistency
  • Session Consistency
Durability Yes Yes Yes Yes Yes
Partitioning Methods Sharding Sharding Sharding Sharding Sharding
Use Cases*
  • Ad Tech
  • Gaming
  • Retail
  • Banking and Finance
  • Media and Entertainment
  • Software and Internet
  • Financial Analysis
  • Internet of Things (IoT)
  • AdTech
  • Web and mobile apps
  • AI solutions
  • IoT apps
  • Social IM
  • Gaming
  • Finance
  • IoT
  • Logistics
  • Mission-critical applications
  • Real-time retail services
  • Real-time IoT device telemetry

 

Supported Data Types*
  • Scalar: Number, String, Binary, Boolean, and Null
  • Multi-Valued: String set, Number Set, and Binary Set
  • Document: List and Map
Treats all data as raw byte strings for most purposes NA
  • String
  • Integer
  • Double
  • Boolean
  • Binary
NA
Latency Microsecond latency with DynamoDB Accelerator (DAX) Consistent sub-10ms latency NA Low latency Read latency for all consistency levels is guaranteed to be less than 10 milliseconds at the 99th percentile
Replication Automated Global Replication Yes NA NA Transparent multi-master replication
Triggers Yes No Yes No JavaScript
Support for ACID transactions Yes Atomic single-row operations No Atomic single-row operations Yes
Data Encryption Yes Yes (data encrypted at rest) Yes (Data encrypted at rest) NA Yes (Data encrypted at rest)
Backup and Restore On-demand backup and restore Available CouchBackup for snapshot backup and restore Custom backup and restoration Automatic and Online Backups
MapReduce No Yes Yes No Yes (with the help of Hadoop Integration)

Points marked asterisk (*) define an inclusive list in the above NoSQL Database Comparison Table

Suggested Reading: Relational Database Comparison – Alibaba, Amazon, Google, IBM and Microsoft

.Picking the right NoSQL database service – tips

NoSQL database services include a wide and comprehensive set of feature-rich solutions to help you build better applications. However, you should not pick a database just because it offers a lot of features. You need to decide what your application and business needs are. Also, you need to consider factors like vendor-lock in to avoid being stuck with a single service provider.

While all the major NoSQL databases we discussed are popular and enterprise-ready, here are a few things you might want to consider when picking a NoSQL service:

  • Define your database goals: Whether you want to store data as a record; build interactive applications requiring real-time data processing; store data for a backend customer application, etc.
  • Consider the security of data: When you trust a service provider with your data, you must ensure that your data is not compromised and is safe and readily available when required.
  • Consider latency: Latency defines the time taken for a web application to respond to a user’s query. For customer-facing applications, you should consider a database that offers the lowest latency.
  • Consider the hosting choice: You can either go for a self-hosted or a managed database service. Again, it depends on your application requirement. For complex and mission-critical applications, managed services come handy.

We hope our NoSQL Database comparison will help you make the right choice.

Feel free to share your queries and feedback through the comment section below.

Disclaimer: The information contained in this article is for general information purpose only. Price, product and feature information are subject to change. This information has been sourced from the websites and relevant resources available in the public domain of the named vendors on 4th September 2020. DHN makes best endeavors to ensure that the information is accurate and up to date, however, it does not warrant or guarantee that anything written here is 100% accurate, timely, or relevant to the website visitors.

Sources:

Page 2 of 2
1 2