A Big, Fast and Persistent Queue

Apr 2, 2013Download as PPTX, PDF10 likes10,354 views

BigQueue is a fast, big, and persistent queue that stores data on disk, making it crash resistant. It allows for concurrent enqueue and dequeue operations in close to O(1) time. The queue can scale to large sizes limited only by available disk space, and provides both consume-once and fanout queue semantics. It uses memory mapping and paging techniques to keep recently accessed data in memory efficiently while accessing the full data set on disk.

BigQueue
A Big, Fast and Persistent
Queue
- by William
http://bulldog2011.github.com/

Feature Highlights
 Fast
 enqueue and dequeue are close to O(1) direct memory access.
 Big
 Only limited by available disk space.
 Persistent
 Data is persisted on disk and is crash resistant.
 Reliable
 OS will be responsible for message persistence even your process crashes.
 Realtime
 Produced messages will be immediately visible to consumers
 Flexible Queue Semantics
 Consume once queue, fanout queue, can even consume by index
 Memory-efficient
 Automatic pagging & swapping algorithm, only most recently accessed data is kept in memory.
 Thread-safe
 Multiple threads can concurrently enqueue and dequeue without data corruption.
 Simple & Light-weight
 Current library jar is less than 40K.

Performance Highlights

 In concurrent producing and consuming case,
average throughput is around 166MBps.
 In sequential producing then consuming case,
average throughput is around 333MBps.

Design – Logical View

 Looks just like a big array or a circular array

Design – Consume Once and Fanout
Semantics Support

Design – Physical View : Paged Index +
Data File

Design – Dynamic View :
Memory Mapped Sliding Window

Concurrency

 Produce(or append) is synchronized in the
queue implementation
 Consume(or read) is already thread-safe

Simple Interface

 Creation
IBigQueue bigQueue = new BigQueueImpl("d:/bigqueue/tutorial",
"demo");
 Enqueue
for(int i = 0; i < 10; i++) {
String item = String.valueOf(i);
bigQueue.enqueue(item.getBytes());
}
 Dequeue
for(int i = 0; i < 5; i++) {
String item = new String(bigQueue.dequeue());
}
 Peek
byte[] data = bigQueue.peek();

Fanout Queue
 Creation
IFanOutQueue foQueue = new FanOutQueueImpl("d:/tutorial/fanout-queue", "demo");
 Enqueue
for(int i = 0; i < 10; i++) {
String log = "log-" + i;
foQueue.enqueue(log.getBytes());
}
 Fanout 1 Dequeue
String fanoutId1 = "realtime";
while(!foQueue.isEmpty(fanoutId1)) {
String item = new String(foQueue.dequeue(fanoutId1));
System.out.println(item);
}
 Fanout 2 Dequeue
String fanoutId2 = "offline";
while(!foQueue.isEmpty(fanoutId2)) {
String item = new String(foQueue.dequeue(fanoutId2));
System.out.println(item);
}
Fanout 1 and Fanout 2 consuming are independent

Use Case 2 :
Big Data Sorting
 Queue Only Algorithm:
1. Put all data into a source queue
2. Build a queueOfSortedQueues by dividing and
sorting the source queue
3. Merge sort the queueOfSortedQueues
4. The last one left in the queueOfSortedQueues
is the final sorted queue

Source, Samples, Docs and Tutorials

https://github.com/bulldog2011/bigqueue

Other Alternatives

 Apache ActiveMQ
 http://activemq.apache.org
 RabbitMQ
 http://www.rabbitmq.com/
 ZeroMQ
 http://www.zeromq.org
 Kestrel
 https://github.com/robey/kestrel
 Apache Kafka
 http://kafka.apache.org

JavaParser is a tool that can parse Java code into an abstract syntax tree (AST), analyze and query the AST to gather metrics and other information about the code, modify the AST to refactor or generate code, and unparse the AST back into Java code. It uses JavaSymbolSolver to resolve symbols in the AST for more advanced analysis and refactoring capabilities. Some potential uses include code generation from templates, running custom code analysis queries, and automated refactoring of code bases. The developers are exploring additional features like comment attribution, lexical preservation of code during refactoring, pattern matching, Java templates, and ways to extend the Java language itself using JavaParser.

Teste de software - Conhecendo e AplicandoAndré Phillip Bertoletti

RESTful writable APIs for the web of Linked Data using relational storage sol...Antonio Garrote Hernández

This document discusses providing RESTful APIs for linked data using relational database storage. It describes translating SPARQL queries to SQL using the R2RML mapping language and exposing RDF graphs through a RESTful interface based on SPARQL HTTP protocol. Key points include mapping RDF quads to relational tables, generating SQL from SPARQL queries, and defining a RESTful API with URI templates mapped to SPARQL endpoints to manipulate named graphs in RDF format. The goal is to help make linked data technologies useful for building web APIs and expose more structured data on the web.

The State Machine CompilerFrançois Perrad

MicroServices architecture @ Ctrip v1.1William Yang

AppDynamics VS New Relic – The Complete GuideTakipi

This document compares the application performance monitoring (APM) tools AppDynamics and New Relic. It discusses their supported languages and environments, key features for backend, frontend, and mobile monitoring, how each tool helps users solve errors, pricing differences, and concludes that AppDynamics is better for on-premise use while New Relic caters more to startups and smaller businesses.

StorageQuery: federated querying on object stores, powered by Alluxio and PrestoAlluxio, Inc.

Alluxio Global Online Meetup August 25, 2020 For more Alluxio events: https://www.alluxio.io/events/ Speakers: Abner Ferreira, Simbiose Ventures Caio Pavanelli, Simbiose Ventures Bin Fan, Alluxio Over the last few years, organizations have worked towards the separation of storage and compute for a number of benefits in the areas of cost, data duplication and data latency. Cloud resolves most of these issues but comes to the expense of needing a way to query data on remote storages. Alluxio and Presto are a powerful combination to address the compute problem, which is part of the strategy used by Simbiose Ventures to create a product called StorageQuery - A platform to query files in cloud storages with SQL. This talk will focus on: - How Alluxio fits StorageQuery's tech stack; - Advantages of using Alluxio as a cache layer and its unified filesystem; - Development of new under file system for Backblaze B2 and fine-grained code documentation; - ShannonDB remote storage mode.

Apache ZooKeeper TechTuesdayAndrei Savu

ZooKeeper is a highly available, scalable, distributed configuration, consensus, group membership, leader election, naming and coordination service. It provides a hierarchical namespace and basic operations like create, delete, and read data. It is useful for building distributed applications and services like queues. Future releases will focus on monitoring improvements, read-only mode, and failure detection models. The community is working on features like children for ephemeral nodes and viewing session information.

Java 7 Features and EnhancementsGagan Agrawal

The document discusses several new features and enhancements in Java 7 including the Fork/Join framework for taking advantage of multiple processors, the new NIO 2.0 file system API for asynchronous I/O and custom file systems, support for dynamic languages, try-with-resources statement for improved exception handling, and other minor improvements like underscores in literals and strings in switch statements.

Alluxio Webinar | What’s New in Alluxio AI: 3X Faster Checkpoint File Creatio...Alluxio, Inc.

Alluxio Webinar Feb. 25, 2025 For more Alluxio Events: https://www.alluxio.io/events/ Speaker: Bill Hodak (VP of Marketing and Product Marketing, Alluxio) Tom Luckenbach (Solutions Engineering Manager, Alluxio) Join us to learn about the latest release of Alluxio Enterprise AI. In this webinar, we’ll provide an overviewof the new features and capabilities of Alluxio Enterprise AI, built to accelerate AI workloads and maximize GPU utilization. Key highlights include: - New caching mode accelerates AI checkpoints - Advanced cache eviction policies provide fine-grained control - Python SDK integrations enhance AI framework compatibility - A demo of Alluxio accelerating AI training workloads in AWS

Project Tungsten: Bringing Spark Closer to Bare MetalDatabricks

As part of the Tungsten project, Spark has started an ongoing effort to dramatically improve performance to bring the execution closer to bare metal. In this talk, we’ll go over the progress that has been made so far and the areas we’re looking to invest in next. This talk will discuss the architectural changes that are being made as well as some discussion into how Spark users can expect their application to benefit from this effort. The focus of the talk will be on Spark SQL but the improvements are general and applicable to multiple Spark technologies.

What’s new in Alluxio 2: from seamless operations to structured data managementAlluxio, Inc.

Alluxio Online Community Office Hours Jan 28, 2020 Speakers: Bin Fan, Alluxio Calvin Jia, Alluxio Alluxio 2.0 release was the biggest update since the birth of the project “Tachyon” from UC Berkley’s AmpLab. Gathering feedback from our Open Source Community and enterprise users, Alluxio 2.0 expands the system in three major directions including improving the operability of the system, having more advanced data management, as well as re-architecting the system to be able to scale to 1 billion + file. The system is now cloud native on AWS, Google Cloud, and allow users to enable native deployment with K8s. The new advanced data management enables data migration and replication from diff storage systems. In this office hour, we introduce what’s new in the Alluxio 2 release, and dive deeper in each major direction the system has expanded on. In this Office Hour, we will go over: - Introduction and motivation of focus areas of Alluxio 2 - Overview of cloud native deployment methods - New data management features - System scalability improvements

Speeding Up Spark Performance using Alluxio at China UnicomAlluxio, Inc.

Fedora Overvieweposthumus

Fedora is an open-source digital object repository system that provides persistent storage and delivery of digital content. It is implemented as a set of Java services and stores content and associated metadata in XML files. The repository can scale to support millions of objects and provides features such as versioning, audit trails and triple store capabilities through integrated systems like Mulgara.

PyCon Estonia 2019Travis Oliphant

dotMemory 4 - What's inside?Maarten Balliauw

Even if your program is just a few lines of code, .NET's runtime will create a number of object in memory. Are all objects being destroyed by the garbage collector? Or is there a potential memory leak? And why is the application seemingly slow when having lots of objects in memory? In this webinar, we'll explore the new dotMemory 4 memory profiler. We'll see why we want to use a memory profiler and how easy it is to use JetBrains dotMemory for that.

Hadoop Vectored IOSteve Loughran

[ACNA2022] Hadoop Vectored IO_ your data just got faster!.pdfMukundThakur22

Since 2006 the world of big data has moved from terabytes to hundreds of petabytes, from local clusters to remote cloud storage, yet the original Apache Hadoop POSIX-based file APIs have barely changed. It is wonderful that these APIs have worked so well, but we can do a lot better with remote object stores, by providing new operations which suit them better, targeted at columnar data libraries such as ORC and Spark. Only a few libraries need to migrate to these APIs for significant speedups of all big data applications. This talk introduces a new Hadoop Filesystem API called "vectored read", coming in Hadoop 3.4. An extension of the classic FSDataInputStream it is automatically offered by all filesystem clients. The S3A connector is the first object store to provide a custom implementation, reading different blocks of data in parallel. In Apache Hive benchmarks with a modified ORC library, we saw a 2x speedup compared to using the classic s3a connector through the Posix APIs. We will introduce the API spec, the S3A implementation, and the benchmarks, and show how to use it in your own applications. We will also cover our ongoing work on providing similar speedups with other object stores, and the use of the API in other applications.

Alluxio Use Cases at Strata+Hadoop World Beijing 2016Alluxio, Inc.

1) Alluxio is an open-source virtual distributed storage system that provides memory-speed access to data across various storage platforms including HDFS, S3, and Swift. 2) Alluxio was presented as having four main use cases - using off-heap memory to alleviate resource pressure, enabling fast data sharing between jobs, accelerating access to remote storage, and providing a unified namespace across different storage systems. 3) Case studies demonstrated that Alluxio improved performance and enabled new workflows, with speedups of 15-300x reported for different customers including Barclays, Qunar, and Baidu.

Reproducibility and automation of machine learning processDenis Dus

Mutexes 2Narendranath Reddy T

Goroutine stack and local variable allocation in GoYu-Shuan Hsieh

The document discusses Goroutine stacks and stack allocation in Go. It explains that each Goroutine has an associated stack that starts small (128 bytes) but can grow as needed by allocating heap memory. There are two stacks - a system stack for M's and a user stack for Goroutines. The user stack uses a free list allocation scheme to efficiently allocate and free fixed-size stacks (e.g. 2KB, 4KB, 8KB). Stack growth is achieved by adjusting pointers when the stack size is exceeded.

Hidden pearls for High-Performance-PersistenceSven Ruppert

Small UseCases with a significant amount of data for internal company usage, most developers had this in their career, already. However, no Ops Team, no Kubernetes, no Cluster is available as part of the solution. In this talk, I will show a few tech stacks that are helping to deal with persistent data without dealing with the classic horizontal scaling tech monsters like Kubernetes, Hadoop and many more. Sit down, relax and enjoy the journey through a bunch of lightning-fast persistence alternatives for pure java devs.

EUDAT Generic Execution FrameworkEUDAT

The document summarizes the EUDAT Generic Execution Framework (GEF). It describes GEF as a framework that allows moving data processing to stored data using containerization. GEF uses Docker containers to package code and dependencies. The document outlines GEF's architecture, current status in development, and example use cases like extracting metadata from stored seismic data. Future plans include a trusted Docker image repository for GEF services.

Kqueue : Generic Event notificationMahendra M

Kqueue is a generic event notification mechanism in BSD that provides a more efficient alternative to select() and poll() for monitoring multiple file descriptors and asynchronous events. It allows applications to register various event types including file descriptor I/O, signals, process state changes, and timers using a single kqueue() system call. When events are detected, it returns only the events that have occurred rather than the full descriptor set, improving scalability. Kqueue has been widely adopted although it is not part of POSIX and third party code may still use select() and poll().

XWiki Rendering @ FOSDEM 2014Vincent Massol

06 file processingIssay Meii

This document discusses file processing and input/output (I/O) in C++. It covers opening and reading from input files, processing the data, writing output to output files, and closing the files. Key points include: 1) The fstream library is used for file I/O, with ifstream for input and ofstream for output. Open is used to connect the file streams to external files. 2) A while loop processes records from the input file by reading values, calculating output, and writing to the output file until the end of file is reached. 3) Constructors initialize file stream objects, and can be overloaded. Do-while loops are not suitable for file processing due

The Pillars Of Concurrencyaviade

The document discusses three pillars of concurrency: 1) Responsiveness and isolation through using background threads to avoid blocking the main UI thread. 2) Throughput and scalability by distributing work across multiple threads to maximize all available CPU cores. 3) Consistency by dealing with shared memory access across threads to prevent race conditions and deadlocks, such as through immutable objects, message passing, and transactional memory.

How Can I use the AI Hype in my Business Context?Daniel Lehner

𝙄𝙨 𝘼𝙄 𝙟𝙪𝙨𝙩 𝙝𝙮𝙥𝙚? 𝙊𝙧 𝙞𝙨 𝙞𝙩 𝙩𝙝𝙚 𝙜𝙖𝙢𝙚 𝙘𝙝𝙖𝙣𝙜𝙚𝙧 𝙮𝙤𝙪𝙧 𝙗𝙪𝙨𝙞𝙣𝙚𝙨𝙨 𝙣𝙚𝙚𝙙𝙨? Everyone’s talking about AI but is anyone really using it to create real value? Most companies want to leverage AI. Few know 𝗵𝗼𝘄. ✅ What exactly should you ask to find real AI opportunities? ✅ Which AI techniques actually fit your business? ✅ Is your data even ready for AI? If you’re not sure, you’re not alone. This is a condensed version of the slides I presented at a Linkedin webinar for Tecnovy on 28.04.2025.

Cyber Awareness overview for 2025 month of securityriccardosl1

More Related Content

Similar to A Big, Fast and Persistent Queue (20)

Java 7 Features and EnhancementsGagan Agrawal

Alluxio Webinar | What’s New in Alluxio AI: 3X Faster Checkpoint File Creatio...Alluxio, Inc.

Project Tungsten: Bringing Spark Closer to Bare MetalDatabricks

What’s new in Alluxio 2: from seamless operations to structured data managementAlluxio, Inc.

Speeding Up Spark Performance using Alluxio at China UnicomAlluxio, Inc.

Fedora Overvieweposthumus

PyCon Estonia 2019Travis Oliphant

dotMemory 4 - What's inside?Maarten Balliauw

Hadoop Vectored IOSteve Loughran

[ACNA2022] Hadoop Vectored IO_ your data just got faster!.pdfMukundThakur22

Alluxio Use Cases at Strata+Hadoop World Beijing 2016Alluxio, Inc.

Reproducibility and automation of machine learning processDenis Dus

Mutexes 2Narendranath Reddy T

Goroutine stack and local variable allocation in GoYu-Shuan Hsieh

Hidden pearls for High-Performance-PersistenceSven Ruppert

EUDAT Generic Execution FrameworkEUDAT

Kqueue : Generic Event notificationMahendra M

XWiki Rendering @ FOSDEM 2014Vincent Massol

06 file processingIssay Meii

The Pillars Of Concurrencyaviade

Java 7 Features and EnhancementsGagan Agrawal

Alluxio Webinar | What’s New in Alluxio AI: 3X Faster Checkpoint File Creatio...Alluxio, Inc.

Project Tungsten: Bringing Spark Closer to Bare MetalDatabricks

What’s new in Alluxio 2: from seamless operations to structured data managementAlluxio, Inc.

Speeding Up Spark Performance using Alluxio at China UnicomAlluxio, Inc.

Fedora Overvieweposthumus

PyCon Estonia 2019Travis Oliphant

dotMemory 4 - What's inside?Maarten Balliauw

Hadoop Vectored IOSteve Loughran

[ACNA2022] Hadoop Vectored IO_ your data just got faster!.pdfMukundThakur22

Alluxio Use Cases at Strata+Hadoop World Beijing 2016Alluxio, Inc.

Reproducibility and automation of machine learning processDenis Dus

Mutexes 2Narendranath Reddy T

Goroutine stack and local variable allocation in GoYu-Shuan Hsieh

Hidden pearls for High-Performance-PersistenceSven Ruppert

EUDAT Generic Execution FrameworkEUDAT

Kqueue : Generic Event notificationMahendra M

XWiki Rendering @ FOSDEM 2014Vincent Massol

06 file processingIssay Meii

The Pillars Of Concurrencyaviade

Recently uploaded (20)

How Can I use the AI Hype in my Business Context?Daniel Lehner

Cyber Awareness overview for 2025 month of securityriccardosl1

TrsLabs - Fintech Product & Business ConsultingTrs Labs

Hybrid Growth Mandate Model with TrsLabs Strategic Investments, Inorganic Growth, Business Model Pivoting are critical activities that business don't do/change everyday. In cases like this, it may benefit your business to choose a temporary external consultant. An unbiased plan driven by clearcut deliverables, market dynamics and without the influence of your internal office equations empower business leaders to make right choices. Getting things done within a budget within a timeframe is key to Growing Business - No matter whether you are a start-up or a big company Talk to us & Unlock the competitive advantage

Splunk Security Update | Public Sector Summit Germany 2025Splunk

Big Data Analytics Quick Research Guide by Arthur MorganArthur Morgan

This is a Quick Research Guide (QRG). QRGs include the following: - A brief, high-level overview of the QRG topic. - A milestone timeline for the QRG topic. - Links to various free online resource materials to provide a deeper dive into the QRG topic. - Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic. QRGs planned for the series: - Artificial Intelligence QRG - Quantum Computing QRG - Big Data Analytics QRG - Spacecraft Guidance, Navigation & Control QRG (coming 2026) - UK Home Computing & The Birth of ARM QRG (coming 2027) Any questions or comments? - Please contact Arthur Morgan at [email protected]. 100% human made.

TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...TrustArc

Most consumers believe they’re making informed decisions about their personal data—adjusting privacy settings, blocking trackers, and opting out where they can. However, our new research reveals that while awareness is high, taking meaningful action is still lacking. On the corporate side, many organizations report strong policies for managing third-party data and consumer consent yet fall short when it comes to consistency, accountability and transparency. This session will explore the research findings from TrustArc’s Privacy Pulse Survey, examining consumer attitudes toward personal data collection and practical suggestions for corporate practices around purchasing third-party data. Attendees will learn: - Consumer awareness around data brokers and what consumers are doing to limit data collection - How businesses assess third-party vendors and their consent management operations - Where business preparedness needs improvement - What these trends mean for the future of privacy governance and public trust This discussion is essential for privacy, risk, and compliance professionals who want to ground their strategies in current data and prepare for what’s next in the privacy landscape.

HCL Nomad Web – Best Practices and Managing Multiuser Environmentspanagenda

Webinar Recording: https://www.panagenda.com/webinars/hcl-nomad-web-best-practices-and-managing-multiuser-environments/ HCL Nomad Web is heralded as the next generation of the HCL Notes client, offering numerous advantages such as eliminating the need for packaging, distribution, and installation. Nomad Web client upgrades will be installed “automatically” in the background. This significantly reduces the administrative footprint compared to traditional HCL Notes clients. However, troubleshooting issues in Nomad Web present unique challenges compared to the Notes client. Join Christoph and Marc as they demonstrate how to simplify the troubleshooting process in HCL Nomad Web, ensuring a smoother and more efficient user experience. In this webinar, we will explore effective strategies for diagnosing and resolving common problems in HCL Nomad Web, including - Accessing the console - Locating and interpreting log files - Accessing the data folder within the browser’s cache (using OPFS) - Understand the difference between single- and multi-user scenarios - Utilizing Client Clocking

Linux Support for SMARC: How Toradex Empowers Embedded DevelopersToradex

Toradex brings robust Linux support to SMARC (Smart Mobility Architecture), ensuring high performance and long-term reliability for embedded applications. Here’s how: • Optimized Torizon OS & Yocto Support – Toradex provides Torizon OS, a Debian-based easy-to-use platform, and Yocto BSPs for customized Linux images on SMARC modules. • Seamless Integration with i.MX 8M Plus and i.MX 95 – Toradex SMARC solutions leverage NXP’s i.MX 8 M Plus and i.MX 95 SoCs, delivering power efficiency and AI-ready performance. • Secure and Reliable – With Secure Boot, over-the-air (OTA) updates, and LTS kernel support, Toradex ensures industrial-grade security and longevity. • Containerized Workflows for AI & IoT – Support for Docker, ROS, and real-time Linux enables scalable AI, ML, and IoT applications. • Strong Ecosystem & Developer Support – Toradex offers comprehensive documentation, developer tools, and dedicated support, accelerating time-to-market. With Toradex’s Linux support for SMARC, developers get a scalable, secure, and high-performance solution for industrial, medical, and AI-driven applications. Do you have a specific project or application in mind where you're considering SMARC? We can help with Free Compatibility Check and help you with quick time-to-market For more information: https://www.toradex.com/computer-on-modules/smarc-arm-family

Generative Artificial Intelligence (GenAI) in BusinessDr. Tathagat Varma

ThousandEyes Partner Innovation Updates for May 2025ThousandEyes

DevOpsDays Atlanta 2025 - Building 10x Development Organizations.pptxJustin Reock

Building 10x Organizations with Modern Productivity Metrics 10x developers may be a myth, but 10x organizations are very real, as proven by the influential study performed in the 1980s, ‘The Coding War Games.’ Right now, here in early 2025, we seem to be experiencing YAPP (Yet Another Productivity Philosophy), and that philosophy is converging on developer experience. It seems that with every new method we invent for the delivery of products, whether physical or virtual, we reinvent productivity philosophies to go alongside them. But which of these approaches actually work? DORA? SPACE? DevEx? What should we invest in and create urgency behind today, so that we don’t find ourselves having the same discussion again in a decade?

How analogue intelligence complements AIPaul Rowe

Artificial Intelligence is providing benefits in many areas of work within the heritage sector, from image analysis, to ideas generation, and new research tools. However, it is more critical than ever for people, with analogue intelligence, to ensure the integrity and ethical use of AI. Including real people can improve the use of AI by identifying potential biases, cross-checking results, refining workflows, and providing contextual relevance to AI-driven results. News about the impact of AI often paints a rosy picture. In practice, there are many potential pitfalls. This presentation discusses these issues and looks at the role of analogue intelligence and analogue interfaces in providing the best results to our audiences. How do we deal with factually incorrect results? How do we get content generated that better reflects the diversity of our communities? What roles are there for physical, in-person experiences in the digital world?

Rusty Waters: Elevating Lakehouses Beyond Sparkcarlyakerly1

Spark is a powerhouse for large datasets, but when it comes to smaller data workloads, its overhead can sometimes slow things down. What if you could achieve high performance and efficiency without the need for Spark? At S&P Global Commodity Insights, having a complete view of global energy and commodities markets enables customers to make data-driven decisions with confidence and create long-term, sustainable value. 🌍 Explore delta-rs + CDC and how these open-source innovations power lightweight, high-performance data applications beyond Spark! 🚀

Increasing Retail Store Efficiency How can Planograms Save Time and Money.pptxAnoop Ashok

Into The Box Conference Keynote Day 1 (ITB2025)Ortus Solutions, Corp

Transcript: #StandardsGoals for 2025: Standards & certification roundup - Tec...BookNet Canada

Book industry standards are evolving rapidly. In the first part of this session, we’ll share an overview of key developments from 2024 and the early months of 2025. Then, BookNet’s resident standards expert, Tom Richardson, and CEO, Lauren Stewart, have a forward-looking conversation about what’s next. Link to recording, presentation slides, and accompanying resource: https://bnctechforum.ca/sessions/standardsgoals-for-2025-standards-certification-roundup/ Presented by BookNet Canada on May 6, 2025 with support from the Department of Canadian Heritage.

SAP Modernization: Maximizing the Value of Your SAP S/4HANA Migration.pdfPrecisely

Procurement Insights Cost To Value Guide.pptxJon Hansen

AI EngineHost Review: Revolutionary USA Datacenter-Based Hosting with NVIDIA ...SOFTTECHHUB

I started my online journey with several hosting services before stumbling upon Ai EngineHost. At first, the idea of paying one fee and getting lifetime access seemed too good to pass up. The platform is built on reliable US-based servers, ensuring your projects run at high speeds and remain safe. Let me take you step by step through its benefits and features as I explain why this hosting solution is a perfect fit for digital entrepreneurs.

Build Your Own Copilot & Agents For DevsBrian McKeiver