Your business is changing. As a finance leader, you know that accounting is a labour-intensive, costly process where
systems often don’t allow for expedient exception handling and many days are fraught with difficulty in matching
invoices to other databases for reconciliation. Like most companies, you know where you want to go but may not have
infrastructure or internal expertise to handle electronic fund transfers, credit card payments or cheque processing— all
the pieces required to make your vision for an efficient, integrated operation a reality.
What if you could reduce the cost of running Oracle databases and improve database performance at the same time? What would it mean to your enterprise and your IT operations?
Oracle databases play a critical role in many enterprises. They’re the engines that drive critical online transaction (OLTP) and online analytical (OLAP) processing applications, the lifeblood of the business. These databases also create a unique challenge for IT leaders charged with improving productivity and driving new revenue opportunities while simultaneously reducing costs.
Modern storage arrays can’t compete on price without a range of data reduction
technologies that help reduce the overall total cost of ownership of external
storage. Unfortunately, there is no one single data reduction technology that fits
all data types and we see savings being made with both data deduplication and
compression, depending on the workload. Typically, OLTP-type data (databases)
work well with compression and can achieve between 2:1 and 3:1 reduction,
depending on the data itself. Deduplication works well with large volumes of
repeated data like virtual machines or virtual desktops, where many instances or
images are based off a similar “gold” master.
Published By: Oracle CX
Published Date: Oct 20, 2017
Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been
top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar
database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as
quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data
from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure
1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP
database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks
can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data.
In-memory databases have helped address p
The Zero Data Loss Recovery Appliance’s benefits
are compelling for any enterprise with a need to
protect critical Oracle databases. The differences
between this database recovery appliance and other
approaches to data protection are stark. The Recovery
Appliance leverages a combination of existing proven
technologies and new developments that eliminate
data loss and improve recovery. The elimination of
periods between backups when database changes are
not captured is also a major benefit, and the movement
to a process of frequent or constant incremental
backups provided by this appliance changes the game.
Published By: Red Hat
Published Date: Jan 01, 2013
IT teams that need high-performing, secure database deployments are turning to Red Hat Enterprise Linux as a foundation for these deployments. Thorough testing and impressive results on industry-standard benchmarks make Red Hat Enterprise Linux a great candidate for operations ranging from high-performance computing to cloud infrastructure.
Published By: MarkLogic
Published Date: Jun 09, 2017
Today, data is big, fast, varied and constantly changing. As a result, organizations are managing hundreds of systems and petabytes of data. However, many organizations are unable to get the most value from their data because they’re using RDBMS to solve problems they weren’t designed to fix.
Why change? In this white paper, we dive into the details of why relational databases are ill-suited to handle the massive volumes of disparate, varied, and changing data that organizations have in their data centers. It is for this reason that leading organizations are going beyond relational to embrace new kinds of databases. And when they do, the results can be dramatic
Published By: MarkLogic
Published Date: Jun 09, 2017
This eBook explains how databases that incorporate semantic technology make it possible to solve big data challenges that traditional databases aren’t equipped to solve. Semantics is a way to model data that focuses on relationships, adding contextual meaning around the data so it can be better understood, searched, and shared. Read this eBook, discover the 5 steps to getting smart about semantics, and learn how by using semantics, leading organizations are integrating disparate heterogeneous data faster and easier and building smarter applications with richer analytic capabilities.
There are five ways to provision test data. You can copy or take a snapshot of your production database or databases. You can provision data manually or via a spreadsheet. You can derive virtual copies of your production database(s).
You can generate subsets of your production database(s). And you can generate synthetic data that is representative of your production data but is not actually real. Of course, the first four examples assume that the data you need for testing purposes is available to you from your production databases.
If this is not the case, then only manual or synthetic data provision is a viable option.
Download this whitepaper to find out more about how CA Technologies can help your business and its Test Data problems.
Data security risk caused by third parties is a pervasive problem.
Yet, many organizations granting remote privileged access to third-party users leave gaps that represent significant security risks.
If you’re like most organizations today, you frequently grant vendors, contractors and other non-staff members access to internal networks and systems. These privileged users remotely administer your operating systems, databases or applications using their own endpoint devices.
Download the eBook to learn the five best practices to control security risk brought on by third parties.
Business leaders expect two things from IT: keep mission-critical applications available and high performing 24x7 and, if something does happen, recover to be back in business quickly and without losing any critical data so there is no impact on revenue stream. Of course, there is a gap between this de facto expectation from nontechnical business leaders and what current technology is actually capable of delivering. For mission-critical workloads, which are most often hosted on databases, organizations may choose to implement high availability (HA) technologies within the database to avoid downtime and data loss.
The CA Performance Management Handbook for DB2 for z/OS by renowned tuning experts Susan Lawson and Dan Luksetich of YL&A covers information to enhance your skills and raise awareness for databases performance management issues and tuning strategies. This supplement to the CA Performance Management Handbook provides specific information on which technologies apply to which issues and how CA Database Management addresses your most pressing database performance management challenges.
Published By: Oracle ODA
Published Date: Aug 15, 2016
Businesses understand more than ever that they depend on data for insight and competitive advantage. And when it comes to data, they have always wanted easy access and fast performance.
But how is the situation different now? Today, organizations want those elements and more. They want IT to strip away the limitations of time with faster deployment of new databases and applications. They want IT to reduce the limitations of distance by giving remote and branch offices better and more reliable access. And in a global world where business never stops, they want IT to ensure data availability around the clock.
If IT can deliver databases and applications faster, on a more automated and consistent basis, to more locations without having to commit onsite resources, IT will be free to focus on more strategic projects.
Published By: Oracle ODA
Published Date: Aug 15, 2016
Oracle added two new models to the Oracle Database Appliance family in addition to the existing high availability model. With an entry list price starting at a fourth of the cost of the prior generation Oracle Database Appliance hardware and flexible Oracle Database software licensing, these new models bring Oracle Engineered Systems to within reach of every organization.
Read about how the Oracle Database Appliance X-6 series expands the reach of the database appliance family to support various workloads, deployment scenarios, and database editions. They are especially designed for customers requiring only single instance databases, but who desire the simplicity, optimization, and affordability of the Oracle Database Appliance. These new models are ideal for customers who seek to avoid the complexity, tuning requirements, and higher costs of “build-your-own” database solutions.
Published By: Datastax
Published Date: Dec 27, 2018
Today’s data volume, variety, and velocity has made relational database nearly obsolete for handling certain types of workloads. But it’s also put incredible strain on regular NoSQL databases. The key is to find one that can deliver the infinite scale and high availability required to support high volume, web-scale applications in clustered environments. This white paper details the capabilities and uses case of an Active Everywhere database
Published By: Quick Base
Published Date: Dec 18, 2017
This eBook reveals how spreadsheets come with hidden risks and costs – and how cost-effective, cloud-based, and customizable no-code databases present a better alternative. Based on a study of 700+ business, operations, and IT professionals, this eBook will help you to improve productivity, enhance decision-making, and centralize data.
TIBCO Spotfire® Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms.
Spotfire Data Science provides a complete array of tools (from visual workflows to Python notebooks) for the data scientist to work with data of any magnitude, and it connects natively to most sources of data, including Apache™ Hadoop®, Spark®, Hive®, and relational databases. While providing security and governance, the advanced analytic platform allows the analytics team to share and deploy predictive analytics and machine learning insights with the rest of the organization, white providing security and governance, driving action for the business.
XtremIO all-flash-arrays (AFAs) have redefined everything you know about SQL Server database infrastructures. Through a ground-breaking, fresh approach to storage design, XtremIO is uniquely engineered for SQL Server database requirements utilizing a powerful and vastly simplified scale-out performance architecture, with in-memory always-on compression, deduplication and space efficient copy services enabling application acceleration, consolidation and agility.
In this white paper, IDC discusses the inherent difficulties associated with traditional backup schemes and the changing dynamics of data protection strategies. We examine Oracle's Zero Data Loss Recovery Appliance (ZDLRA) and the role it can play in providing significantly improved service levels for all types of Oracle databases.
DB2 is a proven database for handling the most demanding transactional workloads. But the trend as of
late is to enable relational databases to handle analytic queries more efficiently by adding an inmemory
column store alongside to aggregate data and provide faster results. IBM's BLU Acceleration
technology does exactly that. While BLU isn't brand new, the ability to spread the column store across
a massively parallel processing (MPP) cluster of up to 1,000 nodes is a new addition to the technology.
That, along with simpler monthly pricing options and integration with dashDB data warehousing in the
cloud, makes DB2 for LUW, a very versatile database.
Traditionally, the best practice for mission-critical Oracle Database backup and recovery was to use storage-led, purpose-built backup appliances (PBBAs) such as Data Domain, integrated with RMAN, Oracle’s automated backup and recovery utility. This disk-based backup approach solved two problems:
1) It enabled faster recovery (from disk versus tape)
2) It increased recovery flexibility by storing many more backups online, enabling restoration from that data to recover production databases; and provisioning copies for test/dev.
At its core, however, this approach remains a batch process that involves many dozens of complicated steps for backups and even more steps for recovery. Oracle’s Zero Data Loss Recovery Appliance (RA) customers report that total cost of ownership (TCO) and downtime costs (e.g. lost revenue due to database or application downtime) are significantly reduced due to the simplification and, where possible, the automation of the backup and recovery process.
Databases tend to hold an organization’s most important information and power the most crucial applications. It only makes sense, then, to run them on a system that’s engineered specifically to optimize database infrastructure.
Yet some companies continue to run their databases on do-it-yourself (DIY) infrastructure, using
separate server, software, network, and storage systems. It’s a setup that increases risk, cost, complexity, and time spent deploying and managing the systems, given that it typically involves at least three different IT groups.
Published By: MarkLogic
Published Date: Mar 13, 2015
Big Data has been in the spotlight recently, as businesses seek to leverage their untapped information resources and win big on the promise of big data. However, the problem with big data initiatives are that organizations try using existing information management practices and legacy relational database technologies, which often collapse under the sheer weight of the data. In this paper, MarkLogic explains how a new approach is needed to handle the volume, velocity, and variety of big data because the current relational model that has been the status quo is not working. Learn about the NoSQL paradigm shift, and why NoSQL is gaining significant market traction because it solves the fundamental challenges of big data, achieving better performance, scalability, and flexibility. Learn how MarkLogic’s customers are reimagining their data to:
- Make the world more secure
- Provide access to valuable information
- Create new revenue streams
- Gain insights to increase market share
- Reduce b
Published By: MarkLogic
Published Date: Mar 17, 2015
You’ve probably heard about NoSQL, and you may wonder what it is. NoSQL represents a fundamental change in the way people think about storing and accessing data, especially now that most of the information generated is unstructured or semi-structured data — something for which existing database systems such as Oracle, MySQL, SQLServer, and Postgres aren’t well suited. NoSQL means a release from the constraints imposed on database management systems by the relational database model.
This free eBook, Enterprise NoSQL for Dummies, MarkLogic Special Edition, provides an overview of NoSQL. You’ll start to understand what it is, what it isn’t, when you should consider using a NoSQL database instead of a relational database management system and when you may want to use both. In addition, this book introduces enterprise NoSQL and shows how it differs from other NoSQL systems, as well as explains when NoSQL may not be the right solution for your data storage problem. You’ll also learn the NoSQ
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