Resources

Transforming Customer Experience With Mongodb Atlas Search

Full-text search is essential for modern applications, but building it is hard. Developers either try to: Contort their database to handle search queries, quickly running up against feature limitations and performance overhead. Bolting on specialized search engines to their database, dramatically increasing the complexity of their application infrastructure. MongoDB Atlas Search gives you a much better way. It combines the power of Apache Lucene — the same technology underpinning the world’s most popular search engines — with the developer productivity, scale, and resilience of the MongoDB Atlas database. A couple of API calls or clicks in the Atlas UI and you instantly expose your data to sophisticated, relevance-based search experiences that boost engagement and improve customer satisfaction. Download this whitepaper to learn more about challenges of implementing search today and how that’s transformed with Atlas Search. We’ll discuss the ideal use cases for Atlas Search, along with those requirements where you may be better served considering alternative approaches. We’ll wrap up with how you can get started with Atlas Search today.

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Thales eSecurity

Thales eSecurity is a leader in advanced data security solutions and services that deliver trust wherever information is created, shared or stored. We ensure that the data belonging to companies and government entities is both secure and trusted in any environment – on-premises, in the cloud, in data centres or big data environments – without sacrificing business agility. Thales provides everything an organisation needs to protect and manage its data, identities and intellectual property, and meet regulatory compliance – through encryption, advanced key management, tokenisation, and privileged-user control and high-assurance solutions. Security professionals around the globe rely on Thales to confidently accelerate their organisation’s digital transformation. Thales eSecurity is part of Thales Group. The Vormetric Data Security platform from Thales eSecurity for MongoDB provides transparent encryption, key management, privileged user access control, and security intelligence. Vormetric can monitor and block non-database users or processes from accessing or viewing the database in a MongoDB environment. Try out Vormetric at the AWS Big Data and Security Test Drive Labs . Fill out the form on this page to download our solutions brief and learn more.

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Dynamic Schema Design

Schema design determines the way an application handles its data. With traditional relational databases, you must define your schema before you can add any data. This inflexibility means you can’t change your schema as your data, application requirements or business evolves. In today’s world hyper-competitive, global business environment, this can hamper your efforts to innovate and stay on top of the competition. NoSQL databases arose to address this limitation by allowing you to insert data without a predefined schema. Because of this, you can easily make changes to an application without interruption. The result is more reliable code integration, faster development, and database administration time. MongoDB provides a document data model that lets you store and combine any type of data while also offering sophisticated data access and rich indexing features. With MongoDB, you don’t have to reinvent the wheel every time your business requirements change or evolve over time. To learn more about MongoDB’s dynamic schema design download the white paper or contact us.

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Evaluating Database Models

When you’re in the design phase of an application, evaluating database models is a critical step in the process. The database model determines the way an application handles data, directly affects the application’s performance and the ability to adapt to changing business requirements. In recent years, new data models have come about as part of the wave of NoSQL databases. These data models were designed to be flexible in order to tackle the large volume and variety of data typically generated by Big Data applications. In contrast, the data models in relational databases are inflexible and ill equipped to accommodate the way applications process data today. When you choose a newer, flexible database model, you benefit from: Being able to change your data model over time to suit your evolving needs Greater efficiency from not having to make time-consuming updates to the existing data in your system Being able to combine data from multiple sources to create a single view of your data MongoDB leads the pack of new database models by offering a document data model that allows for iterative and adaptive data modeling. A flexible schema design lets you incorporate new data into your application without a predefined schema. This allows you to iterate on your application with no interruption or downtime. MongoDB is a database built for today’s always-on, Big Data applications. With MongoDB, you can simplify your design, dynamically modify the database model, and cut down on overall development time. Contact us or download the white paper to learn more about our flexible data model.

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Internet of Things Applications

The future has arrived. Is your database prepared? Technology companies are doing some awe-inspiring things with Internet of Things (IoT) applications. IoT describes technology which connects physical assets and devices together to share information and make life easier and more convenient. IoT devices are processing volumes of data previously unimagined. Bosch, for example, is harnessing data to use in a range of industrial internet of things applications including manufacturing, automotive, retail, and energy. With these sensor-enabled objects, futuristic scenarios have come alive in the ways previously thought impossible. New revenue opportunities abound but only if companies can wrangle that data into something meaningful. Enter MongoDB, the world’s most popular NoSQL database, to help you make sense of sensor data, building internet of things applications never before possible. All this in less time and with less cost than with alternative technologies. The advantages of creating an internet of things application with MongoDB: Document data model. With MongoDB, you can manage and incorporate data in any structure. This allows for you to launch and iterate on your application without having to start from scratch to meet evolving requirements. Inexpensively scale. IoT applications process great volumes of data through sensors so your system will need to scale quickly and cheaply. One of the advantages of MongoDB is the ability to scale out on inexpensive commodity hardware in your data center or in the cloud. Analyze any kind of data with MongoDB. Real-time analysis within the database means you don’t get the time delay you normally would processing data through an expensive data warehouse system. Internet of things applications can spell revolutionary change for your business. Learn more about why IoT is only possible with newer Big Data technology like MongoDB. Download our white paper, Why NoSQL Databases for the Internet of Things: Machina Research, for more insight into the challenges and opportunities for IoT in a rapidly evolving landscape.

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Managing Distributed Data

Today’s generation of databases offers application developers lower cost, greater efficiency, and superior performance in comparison to its more traditional relational counterparts. A key driver behind the lower cost is the ability to scale out your system over commodity hardware. Older relational database technology, on the other hand, is expensive to scale because you need to buy a bigger server to meet the greater volume demand. MongoDB is the leader in a new generation of databases that are designed for scalability. With a technique called “sharding” you are able to easily distribute data and grow your deployment over inexpensive hardware or in the cloud. One of the benefits of scaling with MongoDB is that sharding is automatic and built into the database. This relieves developers of having to build in sharding logic into the application code to scale out the system. Scaling a database system is complex but MongoDB makes it easy. Find out more about the database developers love and the one that enterprises rely on to grow their businesses. Download our white paper today.

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Managing Unstructured Data

Data was pretty straightforward in the days before online applications and mobile devices. Databases processed data in a pre-defined structure of rows and columns contained in tables. This was totally upended with the rise of unstructured data in recent years. By some accounts, unstructured data – think emails, SMS texts, videos, social media posts – makes up more than 95% of all data generated today. The old way of managing data in relational databases, then, is encountering great limitations. Enter NoSQL databases to pick up the challenge of managing unstructured data. MongoDB is the top NoSQL database solution according to DB-Engine rankings, and MongoDB has been downloaded 40 million times and counting. MongoDB’s document data model is particularly well suited for storing unstructured data. It stores all related data together within a single document, and doesn’t require data to fit neatly into the rigid structure of relational rows and columns. Unstructured data can represent both a challenge and an opportunity. Many enterprises have used MongoDB to build applications that could never have been built with relational technology. Learn more about how you can shine by making productive use of your unstructured data and download our whitepaper today.

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MongoDB Benchmark

Application downtime or slow performance could spell disaster for any business. It is essential for companies to proactively monitor and work to ensure high availability and high performance for applications. As part of this strategy, operations teams should establish performance requirements that are continuously monitored to ensure the needs of the business are being successfully delivered to customers. At MongoDB, we take database performance very seriously, and we work to make each release faster and more resource efficient. With MongoDB 3.0, we made major advances in database performance and compared this release to prior releases to understand just how far we had come. Using YCSB, a popular testing framework for database performance, we evaluated a number of workloads on MongoDB 2.6 and MongoDB 3.0. We found greatly enhanced performance over the previous version – anywhere between 7 to 10 times better performance. United Software Associates, an independent third party, also tested MongoDB performance against other database technologies. In their benchmark testing, MongoDB far exceeded other databases in terms of throughput and latency across a number of configurations. There is a reason why MongoDB is the leading database with 40 million downloads and the highest ranking from DB-Engines among NoSQL databases. Find out more about how MongoDB outperforms other leading databases by download the comparative benchmarks.

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MongoDB CMS

Building a content management system (CMS) that stores and serves content to a variety of applications requires the latest technology and development approaches. For the best user experience, the CMS has to handle a large volume of data along with a great variety of unstructured data all in real-time. Typical relational database technology falls short in this area because this kind of database has difficulty incorporating new content, attributes, or features without negatively impacting performance. To address the requirements of modern content management systems you need to turn to the latest database technology that can handle a large volume of unstructured data. MongoDB, the leading database of a new generation of technology called NoSQL, lets you store and serve up any type of content within a single database. You can build these systems with MongoDB quickly and at much less expense than with decades old relational technology. MongoDB is particularly well-suited to support your CMS efforts because the software offers: A ** flexible data model ** means that you can incorporate any kind of data into your CMS, regardless of the source. This flexible model also lets you make frequent updates to the database without downtime to your application. ** Scalable to millions of users ** as MongoDB has a native horizontal scale out architecture that easily lets you accommodate additional demand as your audience grows. ** Much lower cost ** to complete your CMS project as your teams are more productive and you end up spending much less on commodity hardware to scale the system. By some estimates, it costs only 10% of what it would cost with a relational database to build a CMS on MongoDB. MongoDB unites all your content assets into a single database and makes for an overall better user experience. This helps your enterprise stay competitive as customers today expect a seamless experience from your business. Forbes used MongoDB to build a CMS in just 2 months and a new mobile site in just a month. MongoDB helped the publisher gain more insight into the social sharing of their articles so that they were able to capitalize in real-time on content that was going viral. And there are countless other enterprises who have leveraged MongoDB technology for their CMS: eBay used it to build a media metadata storage for their web properties, Pearson employed MongoDB technology to develop a cloud-based learning management system, and Carfax migrated their vehicle history database into a MongoDB CMS and found that they could service 10x more customers as a result. These are just a few examples of companies who take advantage of the database to build powerful MongoDB CMS. Find out more about how MongoDB can help you develop killer apps that will wow your customers – both internal and external alike. Download our white paper today.

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MongoDB Data Loss

Your data is your lifeblood and any loss can spell disaster for your business. Disaster can strike in many unanticipated forms whether it be a natural disaster, fire, or human error. Devoting time and energy to developing a sound backup and recovery strategy then should be a top priority. By planning ahead and putting a backup and recovery plan in place for your deployment, you can restore operations without MongoDB data loss. Backing up your MongoDB deployment to prevent data loss is easy with MongoDB’s suite of management solutions. You can reliably backup and restore MongoDB with Ops Manager for on prem deployments or with Cloud Manager for cloud-based deployments. Both solutions keep your MongoDB database healthy and optimized by converting manual, complex operations tasks into automated procedures. Point-in-time schedule backups are automatically enabled to help you prevent data loss and restore complete running clusters to any point in time with just a few clicks. Cloud Manager currently supports thousands of deployments of varying sizes, from systems using one to hundreds of servers. Organizations who run their deployments with MongoDB Enterprise Advanced can choose between Ops Manager and Cloud Manager. To get started on crafting a sound backup strategy for MongoDB, download our white paper, ** Backup and Its Role in Disaster Recovery. ** The paper covers: Key considerations when evaluating backup strategies Best practices for backing up and restoring your MongoDB data An in-depth comparison of different MongoDB backup methods

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Most Popular NoSQL Database

If you’re looking for the most popular NoSQL database then look no further than MongoDB. It’s the clear leader across several different measures. DB-Engines, which covers over 200 database systems, consistently ranks MongoDB as the most popular NoSQL database from month to month. And for a second year in a row, DB-Engines also named MongoDB the database of the year in 2015 based on several criteria such as social media mentions, the number of jobs created, professional certifications obtained, and Google searches. Gartner, a well-respected research firm, recently recognized MongoDB as a leader in their Magic Quadrant report on operational database management systems in terms of completeness of vision and ability to execute. In addition to these third-party sources, MongoDB’s popularity is evident in the number of software downloads: currently 40 million downloads and growing. MongoDB is loved by developers for its ease of use and by enterprises for addressing a wide variety of use cases. A popular use case for MongoDB is developing a single view from data that would otherwise would sit in silos across the enterprise. Key features that make this possible include: ** Document data model. ** Easily store and combine any type of data while enjoying sophisticated data access and rich indexing features. Incorporate any type of data, no matter what it looks like or where it comes from. ** Dynamic Schema. ** A flexible and dynamic schema allows for quicker iteration and less time spent preparing the data. ** Expressive Query Language. ** Indexing and aggregation capabilities make it possible to find and filter the data and build powerful features from your data. Find out how businesses gain a competitive edge from their data with MongoDB, including examples of successful single view use cases. Download our white paper today.

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NoSQL Database Challenges

Enterprises rely on decades old relational database technology for many good reasons. Relational databases often support long-standing, mission-critical applications and have robust technology and expert support. But as Big Data use cases and applications continually emerge, companies are turning to NoSQL database technology to satisfy their requirements. NoSQL databases offer many benefits over traditional relational technology including a more flexible data model, horizontal scalability, and superior performance. But along with these benefits comes certain NoSQL database challenges. One trade off is the lack of certain fundamental features that make relational databases so useful for generations of applications. Another challenge with NoSQL technology is that many of these databases serve niche use cases and cannot be applied to a broad variety of needs within the enterprise. MongoDB is unique in a crowded field of NoSQL databases. You benefit from all the innovations of NoSQL with MongoDB while still enjoying the fundamentals of relational technology. It is also a general purpose database so you can use MongoDB to address many different use cases. MongoDB offers the features that serve modern applications: Flexible data models that allow you to easily adjust to ever changing requirements Elastic scalability that accommodates varying system demand High performance in terms of throughput and latency While preserving the powerful elements of relational technology: Expressive query language that enables sophisticated use of your data Strong consistency for you to view and process data in real-time Secondary indexes for quick navigation of data Developers love MongoDB for its ease of use and enterprises love MongoDB for its broad applicability to different use cases. If you’re evaluating which NoSQL technology to invest in, read our white paper to better understand the criteria for selecting the right database for your requirements.

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