The relational database has been the foundation of enterprise data management for over thirty years.
But the way we build and run applications today, coupled with unrelenting growth in new data sources and growing user loads are pushing relational databases beyond their limits. This can inhibit business agility, limit scalability and strain budgets, compelling more and more organizations to migrate to alternatives like MongoDB or NoSQL databases.
Seit über 30 Jahren basiert die Datenverwaltung in Unternehmen auf relationalen Datenbanken.
Doch die modernen Verfahren für die Entwicklung und den Betrieb von Anwendungen in Kombination mit der rasant steigenden Zahl neuer Datenquellen und den immer umfangreicheren Workloads der Anwender übersteigen zunehmend die Möglichkeiten relationaler Datenbanken. Die dadurch entstehenden Einschränkungen im Hinblick auf die Flexibilität und Skalierbarkeit sowie die steigenden finanziellen Belastungen bewegen mehr und mehr Unternehmen dazu, zu alternativen Datenbanken wie MongoDB oder NoSQL zu migrieren.
Learn how a Cloudant account can be hosted within a multi-tenant Cloudant cluster, or on a single-tenant cluster running on dedicated hardware hosted within a top-tier cloud provider like Rackspace or IBM SoftLayer.
Published By: Cohesity
Published Date: Aug 09, 2019
As organizations continue to look for ways to increase business agility, a need for a modern database architecture that can rapidly respond to the needs of business is more apparent than ever. While an RDBMS still serves as a lifeline for many organizations, the adoption of technologies such as NoSQL and Hadoop are enabling organizations to best address database performance and scalability requirements while also satisfying the goals of embracing hybrid cloud and becoming more data-driven. And with organizations relying so heavily on these new technologies to yield rapid insights that positively impact the business, the need to evaluate how those new technologies are managed and protected is essential. Hadoop and NoSQL workloads are now pervasive in production environments and require “production-class” data protection, yet few data protection solutions offer such capabilities today.
Published By: Data Stax
Published Date: Apr 27, 2012
This paper examines key data management challenges facing modern businesses and explains how DataStax Enterprise provides the first post-relational database solution to handle real-time, analytic, and search data without using RDBMS solutions.
Since the SQL Access Group created the Call Level Interface, ODBC has become the most ubiquitous method for connecting to relational database sources. ODBC was developed to allow programmers to access relational data in a uniform manner, regardless of the database backend. ODBC translates those generic commands into the specific esoteric commands of the database backend, so the quality of the driver directly determines the performance of the database connectivity layer. Learn more today!
Published By: Datastax
Published Date: Aug 23, 2017
Relational databases had their day and are still viable for certain use cases, but the advent of the cloud and subsequent proliferation of cloud applications is putting an almost unmanageable burden on their capabilities. Read this eBook to learn why your RBMS fails at scale, and why it’s no longer a viable option for today’s distributed, super fast-paced, cloud-friendly world.
Published By: Datastax
Published Date: Aug 07, 2018
Relational databases had their day and are still viable for certain use cases, but the advent of the cloud and subsequent proliferation of cloud applications is putting an almost unmanageable burden on their capabilities. Read this eBook to learn why your RBMS fails at scale, and why it's no longer a viable option for today's distributed, super fast-paced, cloud-friendly world.
Published By: Datastax
Published Date: Aug 15, 2018
"As an Enterprise Architect (or an aspiring one), your job is to help define, build, and manage your company's technology architecture for its single most important asset - its information - in order to meet your company's business goals.
Read this comprehensive guide to learn the ins and outs of designing data management architectures to manage mixed workloads at scale."
Published By: Datastax
Published Date: Apr 08, 2019
For decades, organizations relied on traditional relational
database management systems (RDBMS) to organize, store, and
analyze their data.
But then Facebook came along, and an RDBMS was suddenly not quite enough. The
social giant needed a powerful database solution for its Inbox Search feature, and
Apache Cassandra—a distributed NoSQL database—was born.
Released as an open source project in July 2008, Cassandra—named after the
mythological prophet who famously put a curse on an oracle—became an Apache
Incubator project in March 2009. It graduated to a top-level project in February 2010
In midsize and large organizations, critical business processing continues to depend on relational databases including Microsoft® SQL Server. While new tools like Hadoop help businesses analyze oceans of Big Data, conventional relational-database management systems (RDBMS) remain the backbone for online transaction processing (OLTP), online analytic processing (OLAP), and mixed OLTP/OLAP workloads.
e IBM journey toward unified communications for mobile and social collaboration. Many of today's innovations are driven by the consumer marketplace, and the workplace is no exception. As consumers, we are very familiar with new ways for people to find each other, keepin touch, share ideas and be mobile, getting information from many place. As employees, we would like to apply these consumer capabilities to our work - seamlessly and on a global basis - to make us more productive and effective with business colleagues, clients and business partners. This white paper discusses IBMs infrastructure transformation over the first 12 years, summary value proposition, and volution in supporting mobile devices and BYOD.
If you specialize in relational database management technology, you’ve probably heard a lot about “big data” and the open source Apache Hadoop project. Perhaps you’ve also heard about IBM’s new Big SQL technology, which enables IBM® InfoSphere® BigInsights™ users to query Hadoop data using industry-standard SQL. Curious? This paper introduces you to Big SQL, answering many of the common questions that relational database management system (DBMS) users have about this IBM technology.
Analyst Mike Ferguson of Intelligent Business Strategies writes about the enhanced role of transactional DBMS systems in today's world of Big Data. Learn more about how Big Data provides richer transactional data and how that data is captured and analyzed to meet tomorrow’s business needs. Access the report now.
Securing sensitive data presents a multi-dimensional challenge where complex environments—which often include a wide range of heterogeneous database management systems (DBMS), enterprise applications, big data platforms, file systems, OS platforms with multiple access paths and permission levels—have created a seemingly end-less array of security risks and violation scenarios.
This data security ebook examines the top 5 scenarios and essential best practices for defending against insider threats and external attacks.
Published By: IBM APAC
Published Date: Mar 19, 2018
IDC Analyst Report: A New Breed of Servers for Digital Transformation
Most organizations today are on a digital transformation journey and a server infrastructure is a critical component of that journey. Read the IDC Analyst Report “A New Breed of Servers for Digital Transformation" to find out:
• A roadmap for servers in three stages - from running simple stateless web applications to adopting open source DBMSs to cloud to predictive modeling
• How you can take advantage of OpenPOWER-based infrastructure from a price/performance perspective
• Ways to lower your IT spend and increase your workloads with minimal investment
The demonstrations included in this menu interface show how IBM Tivoli Provisioning Manager solutions can help you manage the complete life cycle of your data center and distributed resources from initial provisioning to patching and configuration maintenance to resource re-purposing or end of life.
Learn about benefits and features of Tivoli Workload Automation Portfolio. Refer to product demos and additional features to know more about specific features, functions and how this portfolio can benefit your organization.
IBM Tivoli Application Dependency Discovery Manager supports the alignment of IT and business with robust and automated application mapping and discovery that helps organizations understand the impact of change and meet compliance needs with detailed reporting and auditing.
Published By: MarkLogic
Published Date: Nov 08, 2016
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. Download now to learn more.
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