We start with Mainframe systems with databases that were built specifically for applications and specific hardware. It was a hierarchical model that required applications to be built in order to get data in and get data out. The 1970’s saw the emergence of the relational model, and the mathematical and theoretical background here is both interesting and if not unique so at least uncommon.The development of SQL databases during the late 1970’s and early 1980 changed the world of database systems completely, and together with other technology changes of those days, such as the emergence of standardized operation systems (most prominently Unix) and the Personal Computer, would transform the climate for compting completely.As the storage capacities of even small computers grew, the potential and uses for databases grew. The PC oriented database systems, simple and working well on small PCs, largely disapperad as PCs became more powerful and above all networked.The 1990 saw the emergence of the Internet, and again the means and needs for accessing data changed, as so did the database systems. Those years also saw data warehousing grow to something everyone could potentially use and benefit from.The emergence of new data types required yet another shift in database models. There is the need to build applications quickly, the need to ingest all types of data quickly and easily without having to adjust schemas. XML databases, document stores all able to manage this new type of data. There are lots of shiny object databases that have popped up to handle this new type of data – but MarkLogic has been doing this for almost 12 years. MarkLogic:Headquartered in Silicon ValleyFounded in 200140% CAGR revenue growth Privately heldPatented, award-winning technology
JPMorgan Chase is one of the oldest financial institutions in the world.Has $2 trillion in assets and 200,000 employees.With its financial exposure with derivatives and the foreign exchange market, it needs to make sure it has a global view of all risk.2.25 million live derivatives, 60,000 new/changed derivatives per day, 1 million foreign exchange tradesPrevious system (on Sybase) was complex with 20 servers.Most banks need many copies because derivatives operate on 5 day schedule, allowing 2 days of downtime for maintenance.Copies of databases are scattered throughout the world.JPMC’s MarkLogic ODS deployment only requires 1 database.It’s global, and runs 24/7/365 with no downtime.They no longer need a separate trading system in other countries, like Saudi Arabia which works on SundayMarkLogic beat both Sybase and Oracle to win the dealFinancial risk is now greatly reduced since JPMC now knows its exact positions, in real time.They achieved a lower cost per trade (not yet quantified).JPMC can make changes to data model in database in hours, while competitors take days, weeks, or months.They drastically reduced maintenance costs, going from 20 systems to 1, 5-10 Sybase DBAs to 1 MarkLogic DBA.No downtime for maintenance gives them a competitive advantage.
This major oil and gas trading company realized it could optimize trading by understanding all factors that influence trading price. They could not get this from their existing system in real-time.MORE INFORMATION---------------------------With a market capitalization of $138 billion, revenue of $297 billion, and nearly 80,000 employees (2010 statistics, most recent available), BP is one of the world’s leading oil and gas companies. In 2010, BP traded twice as much oil as it produced and refined. In a good year, oil trading is a multi-billion dollar addition to the company’s bottom line. The Geographical Energy Map (GEM) application BP used to deliver research to its traders was a legacy application, deployed on a SQL Server. It was a static program with static information – not very valuable in the volatile world of oil trading. The business and technology leaders of BP envisioned building a fully-dynamic application which could take in several sources and formats of information as well as provide real-time alerts to enable better, faster, and more profitable decision-making.MarkLogic beat Oracle, SQL Server, SI
Today, Simon & Schuster has three active implementations of MarkLogic Server. They are:The Syndication Server: This is where the XML versions of Simon & Schuster’s titles are stored. Data about these titles – author, title, publication date, price, etc. – are pushed from MarkLogic Server into whatever formats need the data. For example, publisher’s own online site or to retail partners such as Amazon and Barnes & Noble.The Contracts Server: Simon & Schuster works with thousands of authors, each with a contract specifying different rights. Each contract has been scanned and stored in the company’s SQL Server. MarkLogic works in concert with the SQL Server to track, sort, and make searchable the XML attributes used to describe the rights assigned to the underlying works attached to these contracts. This ensures that the publisher does not violate its agreements in selling and marketing on behalf of its authors.The Layout Server: The most cutting-edge of the three implementations. MarkLogic Server automates what had been a labor-intensive but generic process. Employees would do the time-consuming work of copying all the jacket text of a finished layout – from the cover, to the author bio, to the inside synopsis, etc. and transform it into XML for a Web page. The Layout Server eliminates this step.
This case study is about Nielsen’s BuzzMetrics. They are not in production yet so the account team requests that you do not use their name.Nielsen chose MarkLogic to power its next generation BuzzMetrics Social Media Intelligence platform even though their existing home-grown system currently works. But, they were convinced it would never scale to the level required to handle the explosive growth of social media, especially Twitter. They were also concerned it wouldn’t be agile enough for them to compete in what is rapidly becoming a crowded market. With new competitors entering the Social Media Analytics sector, Nielsen did not want to cede its industry leader status so it was very important to them that they upgrade their platform to state-of-the-art architecture and search that could also easily integrate its intellectual property into customer results.BuzzMetrics measures consumer sentiment by integrating data culled from nearly 100 million blogs, social networks, groups, boards and other consumer-generated media (CGM) which BuzzMetrics blends with its intellectual property. Nielsen embarked on an RFP process in 2011 designed to find the best available “state of the art technology” for their business needs, ultimately resulting in the selection of MarkLogic. We beat out 10 other vendors despite coming in at more than double the cost of the runner up. It is also a true big data win! High velocity, variety - multiple ever-changing content sources/ formats, and high volume data that will ultimately scale to 250TB in the next 3 years. Nielsen will be implementing the initiative in phases, with the initial transaction coming in at $2.7million - $2M License, 400k FYM and $300k services. Here’s why they picked us: 1. Scalability – after extensive due diligence, Nielsen concluded our technology was uniquely capable of handling high volume *and* high query load *and* complex queries all within the high performance levels their clients demand. 2. Best platform for rapid innovation and market adaptability – they felt ML would give them the agility to get to market quickly with innovative new products and features. And that this, coupled with the fact that the ML platform will allow them to “incorporate their own IP,” would give them a competitive edge. 3. Credibility – Prior to our first meeting, many on the Nielsen team had never heard of us and were openly skeptical about our viability as a technology vendor. Over the course of the sales cycle, however, they became very impressed with our stellar technical team and the domain expertise and confidence/leadership exuded. They were also impressed with the other large scale implementations we are powering in the market, e.g. at Lexis and within Federal.
With MarkLogic, they are building a platform that will be able to scale with both an increase in customers and the continued explosive growth of social media communications. They could have continued with their existing system which they felt would not scale with projected volumes or purchased another solution. No other system offered the scalability, agility and search capabilities they sought.
ngmoco:) (short for Next Generation MObile COmpany, the smiley face is part of the name) is a leading mobile games company.Ngmoco makes money by letting users buy virtual goods in their games. They need a financial tracking system to enable transactions and virtual wallets.The volume and velocity of transactions requires a high performance and scalable system.And, the system needs to stay up – downtime means lost transactions and thus lost revenue to ngmoco:).MORE INFORMATION--------------------------ngmoco:) is a mobile gaming company based in San Francisco. ngmoco:) is using MarkLogic as the transaction engine for all in-app purchases and for other money spent in-game. This involves millions of daily trades. For example, ‘We Rule’ players spent 15 million bottles of mojo (in-game currency) every day as of March 2011. That is 5.5 billion per year, and that is only one game in ngmoco’s arsenal. This is a great story to show that MarkLogic is as well suited to manage structured information as it is to deliver unstructured information.Founded in 2008, and owned by DeNA, the leading social games publisher in Japan, ngmoco:) produces free games like the hits We Rule, Touch Pets Dogs & Coin Push Frenzy.Freemium business model generates revenue from microtransactions made when players spend real money in the games. ngmoco:) selected MarkLogic to be the repository for its banking and E-Commerce. That's right, structured information.MarkLogic is the transaction engine for all in-app purchases and for other money spent in productsProcess debit/credit against users’ virtual walletsRecord completed transactions to the ledgerEventually implement a reporting service to feed reports/analytics to financial systemsBig Data: It will involve millions of transactions every day.E.G. ‘We Rule’ players spent 15 million bottles of mojo (in-game currency) every day as of March 2011. 5.5 Billion per year and that is only one game in ngmoco’s arsenal.MarkLogic beat out Oracle for the deal. When asked, “Why did you pick us over Oracle?” A lead engineer who was part of the selection process said, “One, we just don’t like Oracle. Two, MarkLogic fits into our technical philosophy (NoSQL)” Ngmoco:) is already participating in marketingAgreed to participate in speaking opportunity as a MarkLogic customerAgreed to speak to a Gartner analyst about using MarkLogic for structured data Bottom LineBig Data: This story speaks very well to the volume and velocity of Big Data and MarkLogic’s native ability to handle it in real-time. Other Opportunities: Potential to spread further within ngmoco since MarkLogic is now part of ngmoco’s core infrastructure thanks to the banking platform Analytics (eventually): ngmoco is planning to build a reporting service for financial analytics to help further its business strategy.Hot, new, cutting edge company we can use for sales and marketing referencesSolution runs on 6 servers, was a replacement for a MySQL-based prototype
The Bank, built on MarkLogic, handles all of their financial transactions. It ultimately will allow real-time analysis of spending trends to further promote more gaming activity.It replaces a MySQL-based prototype. It’s noteworthy that they implemented MarkLogic to handle highly structured data.Their financial platform powers many games, including the top grossing game on Android and iOS (Rage of Bahamut)MarkLogic is ideal because of its reliability, high performance, scalability, and it fits with ngmoco:)’s technical philosophy of leveraging NoSQL.MORE INFORMATION---------------------------With DeNA, ngmoco:) provides Mobage, a powerful social framework for developers to build and amplify social activity into their games. Underneath their games is ngCore, a powerful technology framework for games to be published and streamed to multiple platforms from a single codebase.
MarkLogic has always been a Powerfully complete and Trusted enterprise ready technology. [click]With MarkLogic 6, we now have a full set of product features that make us the most powerful, accessible and trusted product in the market.(squares that are colored are new features in 6)
The Internet is One of the Biggest Data SetsExcellent source for customer insight and sentimentUnrealized Value in Internal DataReference and market dataCustomer interaction, POS, mobile wallet, etc.OTC Contracts, master netting agreementsTransaction-related communications