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Developer Commu... · Set. 30 7min de leitura

#IoT #InterSystems IRIS #Resource Library

InterSystems IRIS Data Platform is a comprehensive, multi-model, multi-workload data platform that is ideal for accommodating the challenging requirements of applications for the Internet of Things. It is a complete platform for developing, executing, and maintaining IoT applications in a single, consistent, unified environment. It features a distributed architecture to support massive data-ingest rates and data volumes, while providing the flexibility and durability of an enterprise-grade transactional multi-model database to ingest, process, and persist data from a wide range of devices in different formats. It features a complete set of integration, event-processing, and integrated analytics capabilities, including full SQL support and text processing, business process orchestration, and a standards-based development environment.

Connect to, ingest, and persist a wide range of disparate device data types and formats

The data types associated with IoT applications are often heterogeneous, as they may originate from various devices with diverse functions and manufactured by different vendors. The underlying data platform must be able to ingest and process a wide range of raw data types in their original formats. Many applications also require the data platform to persist all of the disparate source data to detect deviations from normal ranges, accommodate downstream ad hoc analytics, maintain regulatory compliance, and fulfill other purposes.

InterSystems IRIS makes it simple and straightforward to connect to any device, using any protocol, both to consume data from devices and to send data or instructions to devices. It provides a variety of capabilities to ensure inbound and outbound connectivity to any device or protocol. It includes a built-in adapter library that provides connectivity and data transformations for traditional industry standards, protocols, and technologies, such as REST, SOAP, HTTPS, and JMS, as well as newer, IoT-specific protocols, like MQTT. InterSystems IRIS also enables the rapid development of custom adapters (and associated business logic) by application developers to support virtually any device or environment.

InterSystems IRIS incorporates a proven enterprise-grade transactional multi-model database that is designed to work with data on a massive scale and provides the flexibility to store the incoming data in the most appropriate format, including:

Schema-free document data models, which can be ideal for storing raw device data (temperature, speeds, etc.) and the associated metadata (timestamp, device ID, etc.) to provide maximum flexibility for performing downstream ad hoc analysis on the data
Multi-dimensional arrays, which can be stored with any number of subscripts
Relational data structures, for well-structured data types
Object-oriented models, for complex data types. The data is described once in a single, integrated data dictionary and is available using object access, high-performance SQL, and multi-dimensional access, all of which can simultaneously access the same data.

Ingest, Process, and Persist Incoming Device Data at High Ingestion Rates

IoT applications must be able to handle massive amounts of data that are being continuously generated by devices, sometimes on the order of hundreds of thousands — or millions — of messages or transactions every second. Traditional databases were simply not designed to accommodate such high data-ingest rates. Consider that fewer than 10 million trades are executed on average each day on the Nasdaq stock exchange. In contrast, a typical smart energy meter application in a small to midsize city must ingest and process more than one billion transactions every day.

InterSystems IRIS is designed to handle incoming data at the extremely high data-ingest rates that are required in IoT environments, in an efficient and cost-effective manner. InterSystems has spent decades optimizing the performance and scalability of its technology to meet the stringent requirements and service-level agreements of its customers.

For example, the European Space Agency uses InterSystems technology to process very large amounts of satellite data at very high ingest rates. Running on one 8-core Intel 64-bit processor, its application ingests and stores five billion discrete Java objects of about 600 bytes each in 12 hours and 18 minutes, at an average insertion rate of 112,000 objects per second.

InterSystems IRIS supports high levels of concurrent access and very large data volumes. Horizontal scaling is available for both on-premise and cloud installations, providing customers with flexible deployment options. Horizontal scaling, where data is shared between nodes, is available via a highly optimized caching protocol that allows the sharing of data among nodes while preserving transactional functionality and integrity.

Integrate Disparate Data, Perform Sophisticated Analyses, and Execute Real-Time Automated Processes

The underlying technology platform must accommodate a range of analytics processing types on the complete, unsummarized historical data, and enable analysts and data scientists to identify correlations among the device data as well as external data sets. This allows the information gleaned from the analyses to be incorporated into real-time programmatic workflows to perform real-time business processes and critical just-in-time actions.

In addition, research has found that between 40 and 60 percent of the business value from IoT applications is gained from interoperability between various IoT applications and systems. Realizing this value requires strong composite application features, as well as strong integration capabilities to combine and correlate data from the different sources to unlock the potential insights that are hidden in disparate data sets.

InterSystems IRIS provides functionality for developing and executing queries and ad hoc analyses on the structured and unstructured data in the database, and it provides consistent, unified access to the data regardless of the object type. The query performance on complex object data structures is extremely fast — typically much faster than relational only databases. In addition to the inherent performance benefits of the multi-model database, bitmap indexing technology further speeds query performance on real-time data.

Analysts and data scientists are able to incorporate a wide range of analytics tools, including predictive modeling, machine learning, Apache Spark, and others, to identify patterns, trends, and correlations in the data sets. The resultant insights or algorithms can be incorporated into the real-time business processes using the graphical modeling environment, to initiate a process or action when specific criteria are met. InterSystems IRIS provides comprehensive capabilities for creating and managing real-time programmatic processes that execute close to the data, in the same engine as the database, for the fastest performance.

In addition, patterns and anomalies in the data can be detected in real time, and programmatic corrective actions, processes, and alerting can be initiated in response.

Key capabilities include:

Messaging and event processing
A business rules engine with a graphical modeling environment
Business process orchestration and management
An adaptable workflow engine that supports automated and human workflows
Composite application development for use (and reuse) within InterSystems applications and with external applications
Business activity monitoring, including graphical dashboards and alerts
Real-time business intelligence, with drag-and-drop creation of data models, real-time dashboards, and the ability to act in real time on information in transactional applications
End-to-end management, including real-time visibility into business processes and system performance

Agility

The technology platform must be agile and developer-friendly, enabling organizations to quickly develop and deploy new applications, and to easily iterate on the applications as requirements and business demands change.

InterSystems IRIS provides a single, unified environment for developing, executing, and maintaining IoT applications. As such, it eliminates the time and work required to learn, use, and integrate multiple disparate tools, products, and open-source projects.

It also provides a plug-in to the popular Eclipse integrated development environment, enabling rapid and open development of IoT applications.

Finally, InterSystems IRIS provides flexible deployment options, supporting both cloud and on-premise deployments.

Conclusion

The Internet of Things is creating unprecedented opportunities for organizations to transform their businesses. But traditional data management technologies and platforms are not equipped to handle the unique requirements, including the high throughput and scale associated with these kinds of applications.

InterSystems IRIS is a comprehensive, multi-model data platform that is ideal for IoT applications. It is a complete platform that provides critical capabilities required to develop, execute, and maintain high-performance IoT applications in a single, consistent, unified environment. It features a distributed architecture to support massive data ingest rates and volumes while providing the flexibility and persistence of an enterprise-grade transactional multi-model database to work with data from a wide range of devices in different formats. It provides a complete set of integration and event-processing capabilities; integrated analytics capabilities, including full SQL support and text processing capabilities; and a standards-based development environment.

InterSystems is the engine behind the world’s most important applications. In healthcare, finance, government, and other sectors where lives and livelihoods are at stake, InterSystems is the power behind what matters. Founded in 1978, InterSystems is a privately held company headquartered in Cambridge, Massachusetts (USA), with offices worldwide, and its software products are used daily by millions of people in more than 80 countries.

Por que engenheiros escolhem IRIS

Multi-modelo, uma máquina. Funciona com tabelas relacionais ,objetos, globais, sem precisar alterar o contexto.
Python onde os dados vivem. O “Embedded Python” permite que você escreva métodos Python server-side que rodam dentro do IRIS (e não por um gateway externo). Você também pode chamar o IRIS do Python usando o móduloiris.
Escalabilidade vertical e horizontal. Inicie em apenas uma instância, e então adicione fragmentos (shards) para dividir o armazenamento e cache horizontalmente em vários nós, para acelerar queries e ingestão.
Feito para aplicações em tempo real. Mira em alta performance para altos volumes de cargas de trabalho, mantendo transações e análises juntas.

Quando o IRIS brilha (e quando não)

Use quando você precisa de cargas de trabalho em estilo HTAP (operacional e analítico em um só lugar), consistência estrita e ferramentas de integração incorporadas. Se você simplesmente precisa de um cache ou um sandbox de análise avulso, uma base de dados maias leve pode ser mais simples.

Mão na massa (≈15 minutos)

1) Suba o IRIS localmente (Docker)

# pull e rode Community Edition
docker run --name iris \
  -d -p 52773:52773 -p 1972:1972 \
  intersystems/iris-community

Portal de Administração Web: http://localhost:52773/csp/sys/UtilHome.csp
As credenciais padrão do container são definidas na primeira execução, siga os prompts da tela.
(Community Edition é gratuita para desenvolvimento e teste e está disponível no Docker Hub, com a documentação oficial do container de "primeiro contato".)

2) Crie uma tabela e consulte(SQL)

No Portal de Administração (System Explorer → SQL), execute:

CREATE TABLE demo.orders(
  id INT PRIMARY KEY,
  customer VARCHAR(80),
  total DECIMAL(10,2),
  created_at TIMESTAMP
);

INSERT INTO demo.orders VALUES
 (1,'Kai',125.50,NOW()),
 (2,'Amaka',78.90,NOW());

SELECT customer, total
FROM demo.orders
WHERE total > 100;

(O IRIS SQL lida com conversões de tipos e formatos lógico/display por baixo dos panos.)

3) Execute o Python dentro do IRIS(Embedded Python)

Crie um método de classe que retorna uma métrica rápida:

Class Demo.Utils
{

ClassMethod BigSpender(threshold As %Numeric) As %Integer [ Language = python ]
{
    import iris
    # Simple count using embedded SQL
    sql = "SELECT COUNT(*) FROM demo.orders WHERE total > ?"
    rs = iris.sql.exec(sql, threshold)
    return list(rs)[0][0]
}

}

Chame-o do terminal:

do ##class(Demo.Utils).BigSpender(100)

Isso é um Python server-side compilado e executado na máquina IRIS (sem ponte externa), e você pode chamar do ObjectScript ou SQL conforme necessidade.

4) Notas sobre escalabilidade (para quando você crescer)

Se as consultas ou ingestão começarem a atingir os limites, adicione shards. O IRIS particiona dados e cache através de nós, fornecendo escalabilidade horizontal sem reescrever - e você pode misturar escalabilidade vertical e horizontal conforme necessidade.

Dicas direcionadas a produção

Mantenha unificado. Resista separar OLTP e análises cedo; o IRIS foi feito para mantê-las juntas até que um gargalo real ocorra.
Use Python com moderação, mas estrategicamente. Coloque lógica de negócio ou analítica que se beneficie das libs do Python no Embeddede Python; deixe o ETL pesado para trabalhos agendados.
Planeje shards antes de necessitar deles. Escolha chaves de shard que você não irá se arrepender (IDs imutáveis, time buckets) e teste em um sandbox de 3 nós.

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Pergunta

Property Buy Re... · Set. 30

#Operação de negócios #Outro

The UK real estate market continues to evolve, offering buyers and investors more ways to secure valuable assets. One of the most effective methods is purchasing an auction property. Unlike traditional sales, property auctions bring speed, transparency, and exciting opportunities to the table. At Property Buy Rent UK, we guide clients through the process, ensuring they take full advantage of this unique buying strategy.

What Is Auction Property?

An auction property refers to real estate sold through a competitive bidding process. Buyers gather in person or online to place bids, and the highest bidder secures the property once the auctioneer’s hammer falls. This approach differs from private negotiations, as the sale becomes legally binding immediately.

The fast-paced structure appeals to buyers who want certainty and efficiency. Instead of waiting weeks for negotiations, auctions finalize sales quickly, typically within 28 days.

Key Advantages of Auction Property

Investing in an auction property offers several benefits:

Speed and Certainty — Transactions move quickly, with fixed timelines and immediate agreements.
Transparency — Open bidding ensures that all parties see the same offers.
Potential Bargains — Many properties sell below their market value, making them attractive to investors.
Variety of Options — Auctions feature everything from residential homes and commercial spaces to land plots.

At Property Buy Rent UK, we remind clients that preparation is vital. With the right strategy, buyers can unlock excellent deals.

Preparing for Auction Success

Success with auction property depends on careful planning. Before bidding, buyers should:

Study Catalogues — Identify promising properties by reviewing auction listings.
Inspect Properties — View properties in person to assess condition and renovation costs.
Check Legal Packs — Review all documents to uncover charges, restrictions, or lease details.
Set a Budget — Avoid overspending by deciding a maximum bid in advance.
Arrange Finances Early — Since completion is quick, buyers need deposits and funding ready.

Property Buy Rent UK offers expert guidance through every step. We help clients evaluate opportunities, understand risks, and bid with confidence.

Online Auction Property

With technology, the concept of auction property has expanded beyond traditional rooms. Online auctions now allow buyers to bid from anywhere, whether at home or abroad.

The advantages of online auctions include:

Real-time bidding from any location.
Access to a wider selection of properties.
Flexible participation without travel.
Opportunities for international investors.

At Property Buy Rent UK, we support buyers in navigating both live and online auctions.Mistakes to Avoid at Auction

While auctions present valuable opportunities, they also come with risks. Common mistakes include:

Emotional Bidding — Letting competition drive prices too high.
Skipping Inspections — Ignoring structural issues can lead to unexpected costs.
Forgetting Extra Costs — Buyers must budget for legal fees, stamp duty, and potential renovations.

Working with professionals like Property Buy Rent UK helps buyers avoid these errors and focus on smart investments.

Who Benefits from Auction Property?

The appeal of auction property stretches across different buyer types:

First-Time Buyers — They can find affordable homes at competitive prices.
Investors — They secure properties with high rental yield potential.
Developers — They purchase renovation projects for resale profit.
Businesses — They acquire commercial property without long delays.

This versatility makes auctions an attractive option for anyone entering the property market.

Why Choose Property Buy Rent UK?

At Property Buy Rent UK, we understand that auctions can feel overwhelming, especially for newcomers. That’s why we provide tailored support:

Property research and selection assistance.
Guidance on reviewing legal documentation.
Financing advice to ensure quick completion.
Effective bidding strategies.
Post-auction support, including renovation or rental advice.

We believe buying an auction property should be exciting, not stressful. Our experience ensures clients feel informed, prepared, and successful at every step.

Conclusion

The UK property market offers countless opportunities, but few are as fast, transparent, and rewarding as buying an auction property. From saving money and securing unique assets to benefiting from a structured process, auctions provide advantages for first-time buyers, investors, and businesses alike.

Still, preparation is key. With the right research and expert guidance, buyers can avoid costly mistakes and maximize opportunities. At Property Buy Rent UK, we specialize in helping clients make confident, informed decisions.

If you are ready to explore the exciting world of auction property, let Property Buy Rent UK be your trusted partner. The right property, at the right price, could be just one bid away.

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Artigo

My Good Movers · Set. 30 3min de leitura

#Outro

Moving can be exciting, but it’s also one of life’s most stressful and financially demanding tasks. Beyond hiring movers and renting trucks, hidden costs, poor planning, and overlooked details can quickly inflate your budget. A data-driven approach can help individuals and families minimize expenses, save time, and reduce stress during relocation.

This guide breaks down the financial, time, and logistical factors of moving, offering actionable strategies backed by data to make your next relocation smarter.

Understanding the Scale of Moving Costs

Each year, approximately 31 million Americans relocate, according to the U.S. Census Bureau. The American Moving & Storage Association reports that:

Average local move costs: ~$1,250
Average long-distance move costs: ~$4,500+

However, these averages exclude numerous hidden costs—packing materials, storage fees, cleaning services, junk removal, and lost productivity—which can significantly increase total expenses.

Data Insight #1: Packing Materials

Packing materials are often underestimated. On average, households spend $100–$300 on boxes, bubble wrap, tape, and protective containers. Specialty items for TVs, artwork, or wardrobes increase costs further.

Strategy: Source free or recycled boxes from local stores or community groups, and use household items like towels or blankets for cushioning. This reduces material costs without compromising safety.

Data Insight #2: Junk Removal Costs

Decluttering before a move is critical for cost management. Removing old furniture, electronics, and unwanted items can be expensive if handled at the last minute.

Services like 1-800-GOT-JUNK provide convenience but vary in cost based on load and location.
1-800-GOT-JUNK Cost can range from $150 to over $600.

Strategy: Begin decluttering weeks in advance. Sell, donate, or recycle items to reduce both junk removal and transportation costs.

Data Insight #3: Storage Fees

Timing mismatches between move-out and move-in dates often lead to storage needs. Storage costs typically range:

Small unit: $50–$200/month
Climate-controlled unit: higher rates

Additionally, movers may charge handling fees for temporary storage.

Strategy: Plan your move dates carefully to minimize or avoid storage. If storage is necessary, compare rates across multiple providers.

Data Insight #4: Cleaning and Utilities

Professional cleaning is often required:

Renters: Cleaning to secure deposit returns
Homeowners: Pre-sale or staging cleaning

Average costs: $150–$300, plus $100–$200 for utility transfers and reconnections.

Strategy: Schedule cleaning and utilities in advance to avoid rush fees. Bundling services or performing basic tasks yourself can reduce costs.

Data Insight #5: Time and Productivity

Time is a hidden cost often overlooked. Studies indicate the average person spends 60 hours preparing for a move. This represents lost productivity and opportunity costs.

Strategy: Use planning apps and checklists (e.g., My Good Movers) to optimize packing, track items, and schedule tasks efficiently. Breaking tasks into manageable steps can minimize disruption to work or daily life.

Actionable Data-Driven Tips

Budget with a Buffer: Add 10–15% extra to cover unforeseen costs.
Declutter Early: Reduce junk removal and truck space.
Research Costs: Reference 1-800-GOT-JUNK Cost to plan ahead.
Leverage Technology: Inventory apps, checklists, and cost calculators improve efficiency.
Align Dates: Schedule move-in/out to minimize storage and downtime.
Monitor Progress: Track milestones to maintain schedule and reduce stress.

Final Thoughts

Managing moving costs isn’t just about dollars—it’s about time, efficiency, and reducing stress. By analyzing data and applying strategic planning, individuals can anticipate hidden expenses, optimize resources, and ensure a smoother relocation.

A structured, data-driven approach transforms moving from a chaotic, costly event into a predictable, manageable process. The combination of budgeting, decluttering, technology, and timing ensures that your next move is both financially sound and operationally efficient.

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Pergunta

Mark Sharman · Set. 30

#Backup #Bancos de dados #Administração do Sistema #HealthShare

At the moment, we have 10 HealthShare instance servers (5 x mirrored pairs), where we implement an External Backup approach, using the freeze/thaw commands against whichever server of the pair is the backup mirror member, to complete a VM level backup. These backups are stored to a disk within our control, to purge as required. This approach allows us to deliver a zero downtime backup approach.

Our future backup solution will be storing immutable backups, with the main concern being that the 10 HealthShare instance servers are quite sizable and that our current approach of backing up the current backup mirror member at the time of the backup could generate 10 immutable VM backups and the size this would consume, when the ideal solution would be to only be capturing one side of each pair consistently.

With this in mind, I don't know whether anybody has any experience in a similar situation as to what would be an optimal solution? I have considered the following options and potential concerns:

1) To only ever backup one side of each pair, with a manual effort to keep one server as the preferred primary - the concerns being if it's the current primary that did get backed up, the freeze/thaw will impact system use, or if there was a VM issue for any period of time, we might have no valid backup

2) Implement online backups of the primary member to a centralised drive location and backup the drive, rather than the entire VM - the concerns being the time to complete such large DB backups, the time to restore and in a DR situation, the time to implement a new VM environment to restore the databases

3) Look at implementing a Concurrent External Backup approach - similar concerns to approach 2

Any thoughts are experiences would be gratefully received.

Regards,

Mark

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InterSystems IRIS Data Platform For IoT Applications

Connect to, ingest, and persist a wide range of disparate device data types and formats

Ingest, Process, and Persist Incoming Device Data at High Ingestion Rates

Integrate Disparate Data, Perform Sophisticated Analyses, and Execute Real-Time Automated Processes

Agility

Conclusion

InterSystems IRIS: o que é, quando usar e um hands-on de 15 minutos

Por que engenheiros escolhem IRIS

Quando o IRIS brilha (e quando não)

Mão na massa (≈15 minutos)

2) Crie uma tabela e consulte(SQL)

3) Execute o Python dentro do IRIS(Embedded Python)

4) Notas sobre escalabilidade (para quando você crescer)

Dicas direcionadas a produção

Auction Property: A Smart Way to Buy and Invest with Property Buy Rent UK

What Is Auction Property?

Key Advantages of Auction Property

Preparing for Auction Success

Online Auction Property

Who Benefits from Auction Property?

Why Choose Property Buy Rent UK?

Conclusion

Managing Moving Costs: A Data-Driven Guide to Smarter Relocation

Move to immutable backups