关系数据库的非关系替代品——通常称为NoSQL数据库——在过去十年中迅速流行起来。2013年，Mon亚博贵宾会贴吧goDB发布了我们最受欢迎的白皮书之一，《评估非sql数据库时的5大考虑事项》。随着技术的发展，我们更新了那篇论文。亚博贵宾会贴吧MongoDB现在提供了一个重大的更新，增加了组织应该考虑的两个新问题:数据库如何处理移动设备在边缘产生的数据，以及数据库如何适应包括搜索和分析在内的更广泛的数据平台。如果您正在测试NoSQL数据库，那么您可能熟悉它们与传统关系数据库的不同之处。关于NoSQL，您已经知道的事情可能是这样的:它们使用不同的数据模型和查询语言。它们有动态模式。他们的规模水平。除了这些常见的特性外，NoSQL数据库之间还有显著的差异。数据模型(文档、图、键值等)查询模型一致性和事务模型api移动数据数据平台商业支持、社区力量和锁定从MongoDB的角度来看，最重要的考虑因素是数据模型。亚博贵宾会贴吧 We popularized the document model , which supports a superset of all data models, making it useful for a wide variety of applications. Key features include the ability to index and query in any field, and the natural mapping of document data structures to objects in modern programming languages. Recent shifts in how modern applications are developed and deployed — and in the experiences they offer customers — highlight the two new considerations. Mobile use cases: Mobile applications introduce the added challenge of not always being connected to the network. Developers need a solution for keeping all their customers’ apps in sync with the back-end database, no matter where they are in the world and what kind of network connection they have. The solution also needs to scale easily and quickly as more users download an app, and support the cutting edge of mobile development technologies as they evolve. Data platform: MongoDB’s application data platform provides developers a unified interface to serve transactional and operational applications alongside search, real-time, and data lake application needs. It eliminates the overhead and friction of developers having to stitch together multiple discrete technologies into a complex architecture, each creating its own duplicated data silo — connected by fragile ETL pipelines — and accessed, secured, governed, and operationalized by different APIs and tools. For a deep dive into all the differences among NoSQL databases, download our white paper, “ Top 7 Considerations When Evaluating NoSQL Databases .”
开发人员的工作有时被视为本质上的战术工作。换句话说，开发人员通常不会被要求制定策略。相反，他们被期望执行战略，表现由“业务”定义的数字体验。但这种情况正在改变。随着许多耗时任务的自动化——从数据库管理到编码本身——开发人员现在能够把更多的时间花在更高价值的工作上，比如理解市场需求或确定需要解决的战略问题。正如他们工作的价值在增加，他们的意见也在增加。因此，许多开发者都在不断发展，从低着头在公司工作的程序员，到具有高度战略眼光的数字体验定义品牌。MongoDB开发关系团队的工程经理Stephen“Stennie”Steneker说:“我认为‘开发者’的定义正在扩大。”亚博贵宾会贴吧“不再只是程序员了。它是任何建造东西的人。” Stennie notes that the learning curve needed to build something is flattening. Fast. He points to an emerging category of low code tools like Zapier, which allows people to stitch web apps together without having to write scripts or set up APIs. “People with no formal software engineering experience can build complex automated workflows to solve business problems. That’s a strategic developer.” Many other traditional developer tasks are being automated as well. At MongoDB, for example, we pride ourselves on removing the most time-consuming, low-value work of database administration. And of course, services like GitHub Copilot are automating the act of coding itself. So what does this all mean for developers? A few things: First, move to higher ground. In describing one of the potential outcomes of GitHub Copilot, Microsoft CTO Kevin Scott said, ““It may very well be one of those things that makes programming itself more approachable.” When the barriers to entry for a particular line of work start falling, standing still is not an option. It’s time to up your strategic game by offering insight and suggestions on new digital experiences that advance the objectives of the business. Second, accept more responsibility. A strategic developer is someone who can conceive, articulate, and execute an idea. That also means you are accountable for the success or failure of that idea. And as Stennie reminded me, “There are more ways than ever before to measure the success of a developer’s work.” And third, never stop skilling. Developers with narrow or limited skill sets will never add strategic value, and they will always be vulnerable to replacement. Like software itself, developers need to constantly evolve and improve, expanding both hard and soft skills. How do you see the role of the developer evolving? Any advice for those that aspire to more strategic roles within their organizations? Reach out and let me know what you think at @MarkLovesTech .
技術和企業是為了維持社會正向發展而存在。我們都有帳單要付，家庭要養，但除此之外，它遠比企業盈利更加重要。我也相信，開發人員尤其對一個組織所能取得的成績，包括社會影響和盈利水準，有著巨大的影響。英國就業與養老金部門的數位團隊劳务和退休金部(数字)是完美典範的團隊,該團隊理解並接受開發者人員在解決重大問題上可以發揮的重要作用。今年,我們有幸與劳务和退休金部数字及其開發人員合作,最終希望能夠應付英國面臨的一些巨大挑戰。就業與養老金部門(劳务和退休金部)是英國最大的公共服務部門。該部門負責向有需要的人提供政府援助，其中包括一系列福利，例如國家養老金、殘疾津貼等。劳务和退休金部超過2200萬位公民依靠每年發放的1680億英鎊維持生計。劳务和退休金部数字團隊負責建置並支援使這一切成為可能的各種應用程式。他們運作1000多個應用程式,並且據估計,他們已經為這些應用程式撰寫了超5000過萬行程式碼。目前,劳务和退休金部的数字正在發生重大轉變,因為大部分最重要的工作已逐漸轉回到內部運作,而開發人員正在採用更敏捷的交付方法。其目標是提供更優質、更高效且更以客為尊的服務；如果沒有一支敬業、熟練和富有創造力的開發人員團隊，他們就無法做到這一點。攻击北朝鲜黑客:MongoDB贊劳务和退休金部助数字的曼徹斯亚博贵宾会贴吧特基地黑客松(单独的)攻击朝鲜對於那些不明就理的人來說,黑客松(单独的)是一項讓開發人員有機會嘗試新技術,解決新問題和試驗新方法的活動。基本上,您會想從黑客松(单独的)中獲得三樣東西:學習新知,玩得開心,以及努力回饋社會。然而,在我們進入黑客松(单独的)之前,有些統計資料表示:曼徹斯特城及其周邊地區有超過75000名失業者在此生活(資料來源:劳务和退休金部的丘吉爾申請,2017年6月),整體失業率高於全國平均水準,居民失業率為5.5%(資料來源:无关,官方勞動力市場統計資料)。科學,研究,工程和技術專業等領域的工作,僅佔曼徹斯特總勞動力的4.69%。然而，該類別的職位空缺占公布的職位空缺總數的 18% (資料來源： 2016/2017 年第一季度市議會經濟儀表板 )。 因此，當 DWP Digital 決定在 2018 年初曼徹斯特數位中心開業之前舉辦一場黑客松(Hackathon)時，他們想要解決的重大挑戰是顯而易見的。Hack the North 是一場為期兩天的公共黑客松(Hackathon)，專注於尋找解決方案，以協助解決該市的失業問題。它通常在場外進行，以便讓使參與者脫離日常活動的思維空間。那裡通常有很多食物 (披薩)、飲料和競爭性的玩笑。 The project board at Hack the North Hack the North 的計畫委員會 由於 DWP Digital 是 MongoDB 在歐洲最重要的使用者之一，而且我們的開發人員宣傳團隊擁有舉辦黑客松(Hackathon)的經驗，因此我們的一些團隊與其他贊助商 ThoughtWorks 及 TechHub Manchester 一起支援這項活動。過去這幾年以來，我參加過好幾次黑客松(Hackathon)，老實說，這是我參加過最精彩的一次。所有參與者的想法、執行力和熱情，都非常的蓬勃煥發。 我們在現場有 70 多人，分為 10 個不同的團隊，每個團隊的任務就是在短短兩天內利用 Churchill (DWP 的公共資料儲存庫 – 也是建立在 MongoDB 上) 等公共來源的可用資料，開發出一個全新的就業解決方案。 "I’d expected DWP to be quite corporate, but the people I’ve met here really want to make a difference to the world.” Our @dtanham on the innovation & creativity on display at our #HackTheNorth #hackathon in #Manchester https://t.co/NPbqhiSy6H pic.twitter.com/t2kmurOa5O — DWP Digital (@DWPDigital) December 11, 2017 最終的解決方案面面俱到、富有創意，並且令人印象深刻。我們擁有一切，從協助新失業者入職過程的引擎，到將簡歷和能力測試遊戲化的平台。然而，最終獲勝者是一支名為 UpSkill 的團隊。UpSkill 採用 MongoDB Atlas 建置了一個應用程式，可以將求職者的技能與雇主的要求配對，還有一個 API 允許求職者存取各種資源來提高他們的技能。這是一個非常靈巧、執行順暢的最終產品，在眾多創意中獨樹一幟。 誠然，我們還沒有完全解決曼徹斯特的失業問題，但在我看來，為期兩天的活動取得了巨大的成功，開發人員學到了很多東西，並建立了一些強而有力的概念驗證。如果想要瞭解更多資訊，請查看 #HackTheNorth Twitter 新聞 ，或我的評委同事 Dan Tanham (DWP Digital 的副主任) 撰寫的這篇優秀 部落格貼文 。 教學相長 直到您可以把所學傳授給別人，才是真正學會了這一課。除了黑客松(Hackathon)之外，DWP Digital 使其團隊保持在開發最佳作法前沿的另一種方式，就是讓他們在開發人員大會上進行演講。我們很高興有數十個 DWP Digital 團隊參加了去年 11 月在倫敦舉行的 MongoDB Europe 2017 ，但真正特別的是 DWP Digital 的首席技術官 Rob Thompson 發表了一整個上午的主題演講。 您可以在下面看到他演講的完整影片，您不會被他的論點所震驚。在概述了 DWP Digital 之後，Rob 談到了 MongoDB 和敏捷開發如何成為協助英國最大的公共服務部門轉變其資料基礎架構，並在養老金、健康、福利和分析方面建置許多旗艦級數位服務的關鍵工具。Rob 堅信，在大多數計畫中，開發人員是決定成敗的關鍵。 在分組討論中，Rob 的同事 David Parry 更詳細介紹了 DWP Digital 如何在雲端中使用敏捷開發、Java 和 MongoDB 來建立微服務架構。這種架構使得從概念驗證快速重複到數百個服務成為可能，因為它們在全國範圍內推出。遺憾的是，我們無法拍攝每場會議，因此如果您想觀看這種類型的演示，您只能親自參加今年稍晚舉辦的 MongoDB Europe。 與 DWP 數位團隊如此緊密合作的幾個月，是一段十分愉快的時光。他們不僅以令人難以置信的強大方式使用 MongoDB，而且更重要的是，我親眼見證了該組織是如何以開發人員為中心的。您可能很難相信大型政府部門會成為開發人員創新的孵化器，但值得慶幸的是，他們確實可以。事實證明，DWP Digital 與矽谷的精英一樣具有前瞻性、敏捷性和以一般使用者為中心的理念，而社會也因此變得更加美好。 在 DWP Digital Jobs Twitter 帳戶 上瞭解有關 DWP Digital 職位空缺的更多資訊，或瀏覽 careers.dwp.gov.uk 。如果您想更深入瞭解 MongoDB 的開發人員重點和我們舉辦的活動，請跟隨我的帳號 @jdrumgoole 。
MDBWOMEN的团队最近举办了一家公司举办了一流的活动演讲者，Maya Leibman，执行副总裁和美国航空公司Cio。玛雅涵盖了广泛的主题，包括她在美国航空公司的27年的职业生涯，她的成功和学习，以及成为美国航空公司技术转型的“空中交通控制器”。Maya Leibman，美国航空公司的执行副总裁和Cio在这里只是玛雅洞里富有洞察力事件的亮点：问题：在世界上最大的航空公司的技术掌舵处是一个非常令人敬畏的姿势。你的角色是什么？答：我一直在美国航空公司27年，在内外和外部技术方面都有很多不同的角色。我在过去的八年或九年内完成了这项工作，我负责所有技术。从开发到基础设施，网络，数据和下一代工具和实践的一切。问：您已被描述为美国技术改造的空中交通管制局。你认为他们是什么意思？答：空中交通管制署负责确保在机场顺利进行一切，这是一个非常复杂的地方。 My team and I have responsibility for ensuring that as we modernize the way we deliver technology that we do it in a safe and secure way and a way that recognizes the risks and seeks to minimize them. We are taking something really complex and making it as smooth as possible. Q: How has COVID impacted your approach to technology innovation? A: It has been impactful in so many different ways. The biggest is in the ways that we are working. Who knew that in the space of a couple of days we would all have to go home and find ways to connect, work and be productive? We would never have thought that it would be as easily done as it was. At American, we say that everyone has a responsibility for innovation. Q: How do you empower different teams and measure how innovative they are? A: What is hard with a big company is that people like consistency, standards, and predictability so processes get built around things and it’s like a fence that prevents innovation. We can’t hire people and put them in a tiny pen because they’ll never achieve what we hired them for. As leaders, we need to have the judgement to understand that while we need standards and consistency, we can’t have it at the expense of people thinking their best thoughts, spreading their wings, and producing new, innovative approaches not just to what we are doing but how we are doing it. (Top left to bottom right: Alexandra Hills , Lacy Ceder , Stephanie Samuels , Maya Leibman ) Q: How has your leadership style evolved over time? A: Every positive attribute you can think of can be used to describe leadership. Personally, for me, it plays on both what your strengths and weaknesses are. One of my strengths is communication. I believe that part of my success as a leader has been the ability to communicate, stand up in front of a group, make compelling arguments and be somebody who can speak confidently with authority and knowledge. One of my weaknesses is listening. I’m not good at it; I interrupt people and am impatient. Honing my leadership skills means trying to get better at the things I’m not good at. Q: You have talked about the JetStream Program quite openly. Why is that and what did you learn from it? A: Jetstream was a disaster. It was a project that my group worked on for two years to develop this system that would re-write our reservation system. During that time, not one line of code was written and that’s how bad it was. We’ve all had experiences in our careers that we are not proud of and I think we should be open about them because it makes us more real and relatable. That’s life. Q: How do you lead your team through those moments of disaster? A: A lot of that has to do with developing an experimental mindset. Technology transformation is all about being willing to experiment and to learn and if it doesn't work, to pivot and do something different. That’s what Agile delivery transformation is all about. When you’re building technology you are doing something that nobody has ever done before so why do you think you are going to get it perfect the first time? Q: You didn’t start at CIO. How did your other roles at American shape you? A: I had ten or 15 jobs in the 27 years and each one has taught me different things. You just extract whatever you can from whatever role you are doing. The one thing I learned is that nothing is linear. We all got to where we are through twists and turns so you have to take your hands off the wheel a little bit and recognize that things are going to come along that you might not have expected. Don’t get too stressed about how your career is going. Everything really works out in the end. Q: Do you have any advice on how women can overcome difficult conversations and negotiations on things like salaries? A: Certain things are endemic to gender and I think it’s important to remember that the men you work with are not hesitating to go to their boss and say they want a review or more money. A lot of women think their work will speak for itself and that they don’t have to put themselves out there but you do have to have those difficult conversations and you do have to get comfortable with being uncomfortable about them. Find a friend and rehearse them before time or have somebody role play with you. We, as women, need to get to a place where we feel confident having those discussions. Q: What has been the biggest challenge in your career and how did you overcome it? A: The merger between American and US Airways was really hard. Hard from a work perspective and also from a people perspective. We were trying to bring two cultures together and two different philosophies around technology. It was a difficult time in a lot of ways. One of the things I insisted on was that we assume positive intention. You have to go into this assuming that everyone is doing the best possible thing. It’s so easy to vilify other people. Q: How do you envision the transition back after COVID? A: People are diametrically opposed on how they think about risk. It’s important when we return to the office to be empathetic with everyone’s re-entry into this process. For me, it’s not about whether we’re going to work from home, it’s about when we are going to work from home. Thank you, Maya for a phenomenal event and for sharing your expertise with the MongoDB community. You are an amazing role model in technology and we appreciate you sharing your insights with us!
随着M亚博贵宾会贴吧ongoDB印度团队的发展，我们希望在Gurugram办公室的全球采购团队中增加新成员。听取人才资源部高级经理Gagan Singh和一些资源团队成员的意见，了解更多关于人才资源者日常工作的信息，以及MongoDB如何提供领导力、促进包容性和促进职业发展。关于采购团队，我们的全球人才资源团队与我们的招聘人员合作，为MongoDB识别和招聘顶级人才。我们按业务部门（销售、工程、客户工程、公司和营销）划分为专门的采购团队，我们的团队致力于支持澳大利亚/新西兰、亚太地区、欧洲和北美的招聘需求。招聘团队与采购团队合作，为空缺职位提供渠道，并组织特别项目，如人才库洞察，以了解人才的可用性，位置分析，以了解招聘的有利位置，以及为空缺职位创建目标公司的组织结构图。作为人才资源提供者，我们的工作是帮助在竞争激烈的市场中找到最好的人才。我们的一天从在Linkedin、Google、Github、Seekout等网站和我们的内部数据库中对人才进行广泛的二次调查开始。然后，我们根据空缺职位所需的技能确定哪些候选人有资格担任该职位。优质候选人档案上传至我们的CRM（候选人关系管理工具）和ATS（申请人跟踪系统），以便进一步审查和推广。除了寻找人才，我们的人才资源团队支持亚太地区的空缺职位，通过电话、电子邮件和InMail与候选人进行接触，以使他们具备招聘人员的资格。该团队还通过研究市场和目标公司的趋势，并根据他们对不同地区的研究得出有用的见解，做出了贡献。这有助于我们成为招聘人员和招聘经理的战略人才顾问。人才来源的成功指标分为领先指标和滞后指标。潜在客户数量、候选人来源和候选人质量是领先指标。人才资源者招聘的、收到录用或被录用的候选人数量是一个滞后指标。听听我们团队的一些成员Ruchi Puri，全球企业和营销资源“成为一名全球资源提供者是非常令人兴奋的。虽然我们每个人都支持特定的业务部门和地区，但我们仍然需要与其他招聘人员和资源提供者合作并制定战略。有一种开放的文化，允许我们为任何事情接触我们的利益相关者和领导者。作为全球企业和营销采购团队的一员，我有能力与来自不同国家和文化的招聘人员合作。最好的是，我们的招聘人员和领导对我们充满信任和信心，随时为我们提供所需的任何支持。“Vivek Negi，全球客户工程资源员”到目前为止，在MongoDB工作是一件愉快的事情，我对数据库市场和软件行业有着丰富的知识。我也有机会访问了我们的纽约市总部，在场外成立了一个员工团队，这使我有机会会见我们的高级领导团队，并与我的利益相关者进行一对一的对话。我很荣幸能与真正聪明的人一起工作。“塔努·萨克塞纳，技术来源R-NA”我在MongoDB工作了三年，这是一段多么美好的旅程。我非常感谢能与这么一群才华横溢、令人惊叹的人一起工作，他们愿意以积极的心态帮助彼此完成伟大的工作。我在以前的公司也曾在类似的机构工作过，但MongoDB的员工真的很棒。在我以前的工作中，我从未感觉自己是与全球利益相关者的一个团队，但在这里，这是一个完全不同的团队，有着惊人的合作伙伴关系。“Kuldeep Pandey，Sourcer-APAC”我于2018年8月加入MongoDB，来自一个机构背景，负责管理一个团队。成为MongoDB的一员是一段伟大的旅程。我曾在不同的业务领域工作，包括北美销售、全球客户工程，现在是印度/亚太地区采购。我于2020年8月从人才资源部晋升为高级人才资源部，在未来几年中，我肯定能为自己找到一条清晰的成长和学习之路。“Yumna Alvi，高级销售资源部-EMEA”我非常自豪能在一家包容多样性、接受各种文化的员工的公司工作。我记得当我开始戴头巾时，我的很多朋友和亲戚都警告我，这可能会影响我的长期职业目标。在获得工商管理硕士学位后，我开始面试，开始我的职业生涯，许多公司对我的着装提出了质疑。这些问题非常令人泄气，我的回答总是‘我捂着头，不是捂着脑袋。’MongoDB从来没有问过我任何事情。相反，他们总是支持和欣赏我，让我亚博科技彩票yabogameting me be myself. In the last two years, MongoDB has provided me with the best opportunities of my life: international exposure, managing stakeholders, mentoring new hires, and interviewing candidates. MongoDB practices its core values every day, especially Embrace the Power of Differences.” Tanya Agarwal, Sr. Sales Sourcer- NA “MongoDB has been a life-changing journey for me. I received two promotions within two years of me joining the company and each level has helped me build on my knowledge. I feel special when I get to know how I am contributing to the growth of MongoDB. Over the past couple of years, I have benefited from the international exposure I have had while partnering with my recruiting counterparts in North America. I have the liberty to make mistakes and I always have the support of my leaders to focus on improvements.” How to succeed on the team We look for individuals with strong research skills, knowledge of LinkedIn Recruiter, and a drive to go above and beyond to find great candidates, especially for niche roles and geographies. If you are applying to be a tech sourcer, you need strong conceptual technical knowledge of topics such as MongoDB fundamentals, products, and competitors; databases; software development lifecycle (SDLC); web services and microservices; DevOps, DataOps, and TechOps; and distributed systems. Experience in sourcing from unconventional tools such as Github is highly desirable. Our interview process involves a live sourcing test followed by interviews with the hiring manager, department head, and stakeholders. For sourcing tests, we ask candidates to read a job description, prepare a boolean based on their understanding of the job requirements, and then run a search. Candidates are assessed on their approach and engagement with the interviewer throughout the conversation, more than the number and quality of search results. The rest of the interview rounds focus on culture fit, relationship building skills, communication, and articulation. Overall, if you have attention to detail, great communication skills (sharing your observations and asking right questions), are research-oriented, and can be creative with boolean strings, we would love to network with you. Interested in pursuing a career on the Talent Sourcing team at MongoDB? We have several open roles and would love for you to transform your career with us!
一年前，在大流行的中间，MongoDB的首席执行官Dev Ittycheria将我作为首席技术官。亚博贵宾会贴吧坦率地说，我以为我知道关于数据库和MongoDB的一切。亚博贵宾会贴吧毕竟，我已经在数据库业务中进行了32年。我一直在MongoDB的亚博贵宾会贴吧董事会，广泛使用了产品。当然，我会完成尽职调查，达到领导团队，并分析了收益报告和产品路线图。即使是所有知识，过去一年都是MongoDB的CTO所教导的，我的许多先入为主的概念都是明白的错误亚博贵宾会贴吧。这让我想知道有多少其他人也可能对这家公司留下了错误的印象。而这篇博客是我试图通过分享去年的四个主要启示来直接设置这些看法。我的第一个启示是MongoDB并不试图成为这一代的关系数亚博贵宾会贴吧据库。多年来，我认为MongoDB基本上希望在成长时是一亚博贵宾会贴吧个更好的，更现代的甲骨文版本。 In other words, compete with the huge footprint of Oracle and other commercial RDBMSs that have been the industry archetype for so long. I was way off. The whole point of MongoDB is to leave all those forms of archaic, legacy database technology in the historical dust. This was never supposed to be an evolution, but instead a revolution. Our founders not only envisioned the world's fastest and most scalable persistent store, but also one that would be programmed and operated differently. The combination of embedded documents and structures combined with automatic high availability and almost-infinite distribution capability all add up to a fundamentally different way of working with data, building applications, and running those applications in production. Oracle and (SQL*Server, etc) still hang their hats on E.F. Codd’s 51-year old vision of rows and columns. To obtain high availability and distribution of data, you need add ons, options packages, bailing wire and duct tape. And you need a lot of database administrators. Not cheap. Even after all that, you’re still trailing the technological edge. This is how wrong I was. Our durable competitive advantages over these legacy data stores make competing with those products almost irrelevant. We instead focus on the modern needs of modern developers building modern applications. These developers need to create their own competitive advantage through language-native development, reliable deployments to production, and lightning fast iteration. And the world is noticing; just check out the falling slope of Oracle and SQL*Server and the rising slope of MongoDB on the db-engines website. Which brings me to my second revelation: MongoDB was built for developers, by developers. I always knew that MongoDB was exceedingly fast and easy to program against. One time while I was bored in a meeting (yes, it happens here as well!), I built an Atlas database, loaded it with 350MB of data, downloaded and learned our Compass data discovery tool, built-in analytics aggregation pipelines, and our Charts package, and embedded live charts in a web page. This took me all of 19 minutes, end to end. To build something like that for engineers , it just has to be built by engineers , ones that are free to focus on all the rough edges that creep into products as features are added. I was first exposed to software planning and management over 40 years ago, and my LinkedIn profile shows a pretty diverse tour around the industry. Now, one year in, I can emphatically state that engineering and product at MongoDB are both different and better than any company I’ve ever had the privilege to work at. Our executive leadership gives engineering and product broad brushstokes of goals and desired outcomes, and then we work together to come up with detailed roadmaps, updated quarterly, that meet those goals in the way we think best, with no micromanagement. And we’re not afraid of 3-5 year projects, either. For example, multi-cloud was more than three years in the making. Also unlike any other company I’ve been at, we embrace the creation and re-payment of tech debt, rather than sweeping it under the rug. We do this through giving our product and engineering teams huge amounts of context, delivered with candor and openness. And one more essential thing; we have an empowered program management team that improves processes (including killing them) as fast as we create them. In short, we paint the targets for our teams and let them decide how and when to shoot. They even design the arrows and bows. It’s true bottoms-up engineering. Our engineers feel valued and understood. And that, in turn, empowers them to develop features that make our customers feel valued and understood, like a unified query language, or real-time analytics and charting directly in the console, or multi-region/multi-cloud clusters where all the networking cruft is taken care of for you. And this brings me to my third revelation: MongoDB is built for even the most demanding mission critical applications. Fast? Yes. Easy? Of course. But mission-critical? That’s not how I saw MongoDB when I used Version 2 for a massive student data project 10 years ago. While it was the only possible datastore we could have chosen for the amount of data and the speed of ingestion and processing needed, it was pretty hard to set up and use in a 24 x 365 environment. MongoDB had gotten ahead of itself in the early 2010’s. There was a gap between our capabilities and the expectations of the market. And it was painful. Other databases had had more than 30 years to solidify their systems and operations. We’d had five. But with Version 3 we added a new storage engine, full ACID transactions, and search. We built on it with Version 4. And then again with Version 5, released this week at our .Live conference. I knew about all this progress intellectually of course when I joined, but not viscerally. I came to realize that the security, durability, availability, scalability, and operability our platform offers (of course in addition to all the features that developers love too) was ideal for architecting fast-moving enterprise applications. And I found the proof in our customer list. It reads like a Who’s Who of major global banks, retailers, and telecommunications companies, running core systems like payments, IoT applications, content management, and real-time analytics. They use our database, data lake, analytics, search, and mobile products across their entire businesses, in every major cloud, on-premises, and on their laptops. And that leads me to my fourth and final revelation. MongoDB is no longer just a database. Of course, the database is still the core. But MongoDB now provides an enterprise-class, mission-critical application data platform. A cohesive, integrated suite of offerings capable of managing modern data requirements across even the most sprawling digital estates, and scaling to meet the level of any company’s ambition, without sacrificing speed or security. Since the day I was first introduced to MongoDB’s products, I’ve had tremendous respect and admiration for the teams and their work. After all, I’m a developer, first and foremost. And it always felt like they “got” me. But had I known then what I know now, I would have jumped on this train a long time ago. In fact, I might have camped out on their doorstep with my resume in hand. And who knows? Maybe a bunch of people reading this will do just that, and have their own revelations about how fulfilling and exciting it can be to be at a great company, with a great culture, producing great products. I’ll write another letter a year from now, and let you know how it’s going then. In the meantime, please reach out to me here, or at @MarkLovesTech .
如果文档数据库市场上存在混淆，它可能与产品的销售方式有关。AWS声称DocumentDB，其文档模型数据库，“随MongoDB兼容性”。亚博贵宾会贴吧但是兼容DocumentDB实际上是如何与MongoDB的问题值得考虑。亚博贵宾会贴吧DocumentDB仅在AWS的基于云的关系数据库中运行时，M亚博贵宾会贴吧ongoDB API仅在亚马逊Aurora的顶部运行。它充其量是一个不一致的模仿者，因为它失败了62％的MongoDB API正确测试。亚博贵宾会贴吧尽管AWS声称与MongoDB 4.0的兼容性，但我们的测试已经得出结论是，其仿真器亚博贵宾会贴吧是我们在2015年发布的MongoDB 3.2的特征的Mishmash。结果是DocumentDB缺乏MongoDB中标准的许多功能。我们已经发布了每个解决方案的功能集的并排比较。在这里，我们将解释一些这些差异在现实世界方案中的一些差异如何，而不是在这里覆盖相同的地面。DocumentDB与Mong亚博贵宾会贴吧oDB头部到头比较比较缩放写入，分区数据和分片本机分片使您可以在多个节点和区域中水平扩展数据库。阿特拉斯提供弹性垂直和水平缩放，以平稳消耗。 DocumentDB does not scale writes or partition data beyond a single node. In order to ensure consistency, MongoDB uses concurrency control measures to prevent multiple clients from modifying the same piece of data simultaneously. Replicate and scale beyond a single region A number of factors are driving the need to distribute workloads to different geographic regions. In some cases, it’s to reduce latency by putting data closer to where it’s being used. In other cases, it’s to store data in a specific geographic zone to help meet data localization requirements. Finally, there’s the need to ensure the availability of data when there’s an outage of an entire AWS region. The flexibility to replicate and move workloads as needed is increasingly seen as a business requirement. But by default DocumentDB limits you to just 15 replicas and constrains you to a single region. Newly introduced Global Clusters may look like an answer, but much like “MongoDB compatibility,” it’s potentially misleading. The Global Clusters feature more closely resembles multi-region replication since it only allows writes to single primaries instead of being able to write to multiple regions. It also requires manual reconfiguration to recover from failures, making it a partial solution, at best. MongoDB Atlas allows true global cluster configurations so you can deliver capabilities to all your users around the world. At a click of a button, you can place the most relevant data near local application servers across more than 80 global regions to ensure low-latency reads and writes. By being able to define a geographic location for each document, your teams are able to more easily meet local privacy and compliance measures. It’s also an insurance policy against being locked into a single public cloud provider. High resilience, rapid failover, retryable writes For critical applications, every second of downtime represents a loss of revenue, trust, and reputation. Rapid failover to a different geographic area is necessary when recovery time objectives (RTO) are measured in seconds. DocumentDB failover SLAs can be as high as two minutes, and multi-region failover is not available. With MongoDB, failover time is typically five seconds, and failover to a different region or cloud provider are also options. Write errors can be as costly as downtime. If a write to increment a field is duplicated because a dropped connection failed to notify the client that the write was executed, that extra increment can be very costly depending on what it represents. With retryable writes, a write can be sent multiple times but applied exactly once. MongoDB has retryable writes. DocumentDB doesn’t. Integrated text search, geospatial processing, graph traversals Integrated text search saves time and improves performance because you can run queries across multiple sources. With DocumentDB, data must be replicated to adjacent AWS services, which increases cost and complexity. MongoDB Atlas combines integrated text search, graph traversals, and geospatial processing features into a single API and platform. Integrated search with MongoDB Atlas helps drive end user behavior by serving up relevant results based on what users are looking for or what businesses want to direct them toward. Hedged reads Geographically distributed replica sets can also be used to scale read operations and intelligently route queries to the replica set that’s closest to the user. Hedged reads is a function that automatically routes queries to the two closest nodes (measured by ping distance), returning results from the fastest replica. This helps minimize situations where queries are waiting on a node that’s already busy. DocumentDB doesn’t offer hedged reads, and it’s more restricted in terms of the number of replica sets it allows and the ability to place workloads in different regions. MongoDB gives you more flexibility when distributing data geographically for hedged reads since it leverages all of the major public cloud providers. Online Archive Putting data in cold storage can be a death knell if accessing it again is too cumbersome or slow. With online archiving, you can tier data across fully managed databases and cloud object storage and query it through a single endpoint. Online archiving automatically archives historical data while reducing operational and transactional data storage costs without compromising on query performance. MongoDB has it. DocumentDB doesn’t. Integrated querying in the cloud Running separate queries for separate data stores can drain resources and slow queries. The best solution is being able to query and analyze data across all the different databases and storage containers at once. You can do this with integrated querying, where you run a single query to analyze live cloud data and historical data together and in-place for faster insights. With DocumentDB, you have to replicate data to adjacent AWS services. With MongoDB, you can query and analyze data across cloud datastores and MongoDB Atlas in its native format. You can also run powerful, easy-to-understand aggregations through a unified API for a consistent experience across data types. On-demand materialized views When you create aggregations, the results are usually put into a new collection every time you create it. The entire collection is regenerated each time you create the aggregation. This process consumes CPU and I/O. With the $merge stage, you can just update the generated results collection rather than rebuild it completely. $merge lets you incrementally update the collection every time you run it. To update it, all you need to do is run the aggregation again and it will update all the values in place. $merge gives you the ability to create collections based on an aggregation and update those collections efficiently. This functionality allows users to create on-demand materialized views, where the content of the output collection is incrementally updated when the pipeline is run. MongoDB has this capability. DocumentDB does not. Rich data types The decimal data type is critical for storing very large or small numbers, like financial and tax computations, where it’s necessary to emulate decimal rounding exactly. DocumentDB does not support decimal data types or, in turn, lossless processing of complex numeric data, which is a problem for financial and scientific applications. MongoDB does support rich data types like Decimal128, giving you 128 bits of high precision decimal representation. Client-side field-level encryption Client-side field-level encryption (FLE) reduces the risk of unauthorized access or disclosure of sensitive data, like personally identifiable information (PII) and protected health information (PHI). Fields are encrypted before they leave the application, which protects data while in transit over the network, in database memory, at-rest in storage, in backup repositories, and in system logs. DocumentDB does not offer client-side FLE. MongoDB’s client-side FLE provides among the strongest levels of data privacy and security for regulated workloads. Platform agility In addition to the feature sets described here, one of the biggest differences between DocumentDB and MongoDB is the degree of freedom you have to move between different platforms. AWS offers seamless movement and minimal friction between services within its own ecosystem. MongoDB makes it easy to replicate data or move workloads to any cloud provider, giving you complete flexibility within the AWS platform as well as outside of it — whether it’s a self-managed MongoDB instance on cloud infrastructure, a full on-premises deployment, or just a local development instance on an engineer’s laptop. Try MongoDB Atlas for free today!
Mong亚博贵宾会贴吧oDB的创新奖旨在表彰项目和谁远大的梦想的人。他们庆祝开创性的使用数据来构建有吸引力的应用和专业人士拓展技术与MongoDB的限度的创造性。亚博贵宾会贴吧今年，该公司收到的条目跨越几十个行业，从破坏性的，新兴的初创公司业界领先的全球性企业。我们很高兴地宣布，12个赢家谁正在MongoDB.live在今年兑现。亚博贵宾会贴吧威廉·左拉奖：迈克尔·奥莱 - 一个独立的软件架构师，系统集成商和后端开发者，迈克尔是第一个MongoDyabogame亚博科技彩票B的冠军赢得了难得的长青论坛徽章，他坚定的MongoDB的社区的支持。亚博贵宾会贴吧双认证既是MongoDB的开发人员和DBA，迈克尔亚博贵宾会贴吧慷慨地分享了他在MongoDB的论坛各级社区成员的专业知识。他还组织达赫虚拟社区用户组，甚至还抽出时间与#BuildTogether MongoDB的员工进行演讲并在网上流聊天。亚博贵宾会贴吧迈克尔是第一次出国之一，自2014年以客户为先奖上的MongoDB项目咨询：亮度健康 - 作为COV亚博贵宾会贴吧ID-19由席卷全球，亮度卫生跳进行动，合作伙伴，卫生系统和供应商能够充分利用自己的平台运行一些大型的大规模疫苗接种地点和帮助诊所的规模从数百到数千约会，最终导致近200万人接种约会。数据好奖：食品之旅 - 这家公司解决了食品科学和供应链效率低下的软件，以帮助企业器8十亿人更好。亚博科技彩票yabogame To date, Journey Foods has established a database of over 11 billion ingredient insights. From Batch to Real Time Award: CSX - A leading provider of transportation and supply chain solutions, CSX is redefining freight rail. Embracing event-driven architecture, the company has improved engagement with safety information produced by Positive Train Control (PTC) systems by putting PTC data on MongoDB. Leveraging MongoDB, CSX receives the data real-time – enabling smarter and faster decision making and better ensuring safety regulations are met for the company’s around-the-clock operations. Front Line Heroes Award: Ahmad Awais for The “CORONA CLI” Project - Awais built a CLI command-line tool to track COVID-19 in March 2020. As COVID-19 spread, the project termed “corona-cli” became the number one trending repository on GitHub. To date, this project has served several billions of API requests making COVID stats accessible throughout the world with 53 different releases and extensive functionality built/contributed by 15+ developers. Going Global Award: Riot Games - Founded in 2009 to change the ways games were developed, Riot has created the most-played PC game in the world and expanded to 20+ offices worldwide in only 12 years. A game platform developer and his team migrated their data to MongoDB Atlas to manage B2B billing and player IP validation data for all of their games globally. Industry Transformation Award: American Airlines - As a network air carrier, American’s purpose is to care for people on life’s journey. During COVID-19, American Airlines passionately pursued efficiencies, particularly those enabled by technology. American Airlines created an operational data layer on MongoDB in the cloud for critical flight information, which enabled other services to move to the cloud and consume data from the modern cloud-based data fabric. Jackpot Award: Cisco Systems - Cisco is the worldwide leader in technology that powers the Internet. This global brand completed the Cloud native migration of its highly critical Commerce Quoting platform, which serves more than 225K users and 4M application hits daily worldwide. The result has been no application downtime for releases, improved performance, lower TCO, and significantly better developer productivity. Savvy Start-Up Award: Blerp - The audio expression platform that makes it easy to enhance any moment with sound clips. Millions of Blerps are being shared on their two largest integrations on Twitch and Discord. Unbound Award: Yodel - Yodel is an independently owned parcel carrier, delivering around 190 million parcels each year for many of the UK’s leading retailers and businesses. An early adopter of Realm Sync following its GA release in February 2021, Yodel uses MongoDB to sync parcel-scanning data from employee devices up to Atlas - and in the opposite direction, pushing down large data volumes to devices via the MongoDB Kafka Connector. By streamlining the process of scanning parcels and reducing the time drivers need to spend in service centers, Yodel expects to achieve increased productivity and cost savings. Certified Professional of the Year Award: Sydney Herrera - After becoming certified and while assisting a large governmental organization in a mainframe modernization effort - which involved transforming multiple massive, disparate mainframe datastores into a cohesive and application-focused MongoDB data warehouse, Sydney was faced with the challenge of assisting developers with building efficient applications. He created a tool called proactive query analyzer (PQA) that was rolled out into the organization. PQA is an automated tool that analyzes queries sent to MongoDB and provides feedback and suggestions before queries are implemented to aid developer teams. For the People Award & Innovator of the Year Award: The Department for Work and Pensions (DWP) is the UK’s biggest public service department responsible for distributing over £190 billion annually in welfare, pensions and child maintenance to over 20 million citizens. With an unprecedented spike in demand due to the COVID-19 crisis, the Universal Credit platform was able to scale seamlessly, underpinned by MongoDB databases, to meet the tenfold spikes in claims from people who needed DWP’s support. The information contained in the above descriptions was provided by the relevant award winners or obtained from publicly available information.