big sql

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Published By: MarkLogic     Published Date: Jun 17, 2015
Modern enterprises face increasing pressure to deliver business value through technological innovation that leverages all available data. At the same time, those enterprises need to reduce expenses to stay competitive, deliver results faster to respond to market demands, use real-time analytics so users can make informed decisions, and develop new applications with enhanced developer productivity. All of these factors put big data at the top of the agenda. Unfortunately, the promise of big data has often failed to deliver. With the growing volumes of unstructured and multi-structured data flooding into our data centers, the relational databases that enterprises have relied on for the last 40-years are now too limiting and inflexible. New-generation NoSQL (“Not Only SQL”) databases have gained popularity because they are ideally suited to deal with the volume, velocity, and variety of data that businesses and governments handle today.
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data, data management, databse, marklogic, column store, wide column store, nosql
    
MarkLogic
Published By: MapR Technologies     Published Date: Mar 29, 2016
Add Big Data Technologies to Get More Value from Your Stack Taking advantage of big data starts with understanding how to optimize and augment your existing infrastructure. Relational databases have endured for a reason – they fit well with the types of data that organizations use to run their business. These types of data in business applications such as ERP, CRM, EPM, etc., are not fundamentally changing, which suggests that relational databases will continue to play a foundational role in enterprise architectures for the foreseeable future. One area where emerging technologies can complement relational database technologies is big data. With the rapidly growing volumes of data, along with the many new sources of data, organizations look for ways to relieve pressure from their existing systems. That’s where Hadoop and NoSQL come in.
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MapR Technologies
Published By: CapTech     Published Date: May 26, 2015
Big Data is the future of business. According to CloudTweaks.com, as much as 2.5 quintillion bytes of data are produced each day, with most of this data being captured by Big Data. With its ability to transfer all data sources all into one centralized place, Big Data provides opportunities, clearer visions, customer conversations and transactions. However, with the dazzling big promise of Big Data comes a potentially huge letdown. If this vast pool of information resources is not accessible or usable, it becomes useless. This paper examines strategies for building the most value into your Big Data system by enabling process controls to effectively mine, access and secure Big Data.
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big data, captech, data, data management, nosql
    
CapTech
Published By: FairCom     Published Date: May 25, 2016
As companies embrace NoSQL as the “next big thing,” they are rightly cautious of abandoning their investment in SQL. The question a responsible developer or IT manager must investigate is “in which cases are each of these technologies, SQL and NoSQL, the appropriate solution?” For example, cloud provider BigStep offered this assessment: “NoSQL is not the best model for OLTP, ad hoc queries, complicated relationships among the data, and situations when stability and reliability outweigh the importance of speed.” While that statement may be true of many NoSQL databases, c-treeACE is the exception. Its unique, No+SQL architecture offers the advantages of SQL on top of a robust, high-performance NoSQL core engine. In this white paper, you'll read five ways c-treeACE breaks the NoSQL mold in terms of: • Data Integrity • Availability and Reliability • Complex Data Relationships • Flexible Queries • Performance
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FairCom
Published By: Basho     Published Date: Nov 25, 2015
The landscape of Scalable Operational and Analytical Systems is changing and disrupting the norm of using relational databases for all workloads. With the growing need to process and analyze Big Data at Scale, the demand for alternative strategies has grown and has given rise to the emergence of NoSQL databases for scalable processing. Mike Ferguson, Managing Director of Intelligent Business Strategies, is an independent IT Analyst who specializes in Big Data, BI/Analytics, Data Management and Enterprise Business Integration. In this whitepaper he will discuss the movement towards NoSQL databases for scalable operational and analytical systems, what’s driving Big Data analytics from Hadoop to the emergence of Apache Spark, the value of operational analytics and the importance of in-memory processing, and why use Apache Spark as your in-memory analytical platform for operational analytics.
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Basho
Published By: birst     Published Date: Jan 21, 2013
This Dive Deep analyst report looks at the process of building an environment for what can be aptly termed Agile Business Analytics.
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data, data management, data governance, big data, cloud, business intelligence, semantic technology, nosql, information quality, data quality, metadata, enterprise information management, master data management, mdm, analytics, database
    
birst
Published By: SAP     Published Date: Jan 23, 2013
This paper examines the root causes of data centralization failure and then reviews straightforward best practices that can help avoid such failures but are typically ignored when systems are designed in an ad hoc, organic manner.
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data, data management, data governance, big data, cloud, business intelligence, semantic technology, nosql, information quality, data quality, metadata, enterprise information management, master data management, mdm, analytics, database
    
SAP
Published By: MarkLogic     Published Date: Jun 16, 2013
The primary issue discussed within this paper boils down to two disparate database reliability models: ACID vs BASE. The first (ACID) has been around for some 30+ years, is a proven industry standard for SQL-centric and other relational databases, and works remarkably well in the older, yet still extant, world of vertical scaling. The second (BASE) has only recently gained popularity over the past 10 years or so, especially with the rise of social networking, Big Data, NoSQL, and other leviathans in the new world of Data Management. BASE requirements rose out of a need for ever-expanding horizontally scaled distributed networks, with non-relational data stores, and the real-time availability constraints of web-based transaction processing. While there are now more crossovers and negotiations between the two models, they essentially represent two competing groups, with Brewer’s CAP Theorem acting as the referee in the middle forcing tough decisions on each team.
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data, data management, unstructured data, nosql, database, acid, base, database transactioning
    
MarkLogic
Published By: Sqrrl Data, Inc.     Published Date: Jun 02, 2014
With the dissolution of the “trusted zone”, Data-Centric Security is a key enabler for Big Data applications. Sqrrl's Enterprise is a NoSQL database that is built with a Data-Centric Security implementation that includes cell-level security labeling and enforcement, encryption at rest, encryption in motion, an automated data labeling engine, a security policy specification engine, custom secure search indexing, and an audit facility.
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Sqrrl Data, Inc.
Published By: AstuteIT_ABM_EMEA     Published Date: Feb 01, 2018
Why Read This Report The demand for databases is on the rise as organizations build next-generation business applications. NoSQL offers enterprise architecture (EA) pros new choices to store, process, and access new data formats, deliver extreme web-scale, and lower data management costs. Forrester’s 26-criteria evaluation of 15 big data NoSQL solutions will help EA pros understand the choices available and recommend the best for their organization. This report details our findings about how each vendor fulfills our criteria and where they stand in relation to each other to help EA.
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nosql, market, industries, strategy, presence, vendor
    
AstuteIT_ABM_EMEA
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
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enterprise, nosql, relational, databases, data storage, management system, application, scalable, enterprise applications, data management
    
MarkLogic
Published By: Red Hat, Inc.     Published Date: Jul 10, 2012
Today, as IT departments struggle to design and implement solutions capable of managing exponential data growth with strict requirements for application scale and performance, many of them are turning to in-memory data grids (IMDGs).
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it departments, data growth, managing data growth, application scale, application performance, in-memory data grids, imdgs, big data, data volume, data velocity, data variability, data management, data collection, data processing, data scaling, data storage systems, data access, data solutions, data challenges, management tooling
    
Red Hat, Inc.
Published By: Red Hat, Inc.     Published Date: Jul 10, 2012
Is data changing the way you do business?Is it inventory sitting in your warehouse? The good news is data-driven applications enhance online customer experiences, leading to higher customer satisfaction and retention, and increased purchasing.
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it planning, data, data-driven applications, data challenges, data solutions, big data solutions, big data challenges, in-memory databases, web-abpplications, in-memory data grid, nosql, storage nodes, e-commerce applications, social applications, logisitcs applications, trading applications, data scaling, rest, memcached, hot rod
    
Red Hat, Inc.
Published By: OpTier     Published Date: Mar 11, 2013
In the Information Technology (IT) industry, 2012 has been the year of Big Data. From a standing start toward the end of the last decade, Big Data has become one of the most talked about topics.
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optier, big data, enterprise data warehouse, edw, nosql, business technology
    
OpTier
Published By: AstuteIT_ABM_EMEA     Published Date: Feb 02, 2018
The demand for databases is on the rise as organizations build next-generation business applications. NoSQL offers enterprise architecture (EA) pros new choices to store, process, and access new data formats, deliver extreme web-scale, and lower data management costs. Forrester’s 26-criteria evaluation of 15 big data NoSQL solutions will help EA pros understand the choices available and recommend the best for their organization. This report details our findings about how each vendor fulfills our criteria and where they stand in relation to each other to help EA.
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nosql, market, industries, strategy, presence, vendor
    
AstuteIT_ABM_EMEA
Published By: Datastax     Published Date: Apr 04, 2017
As the big data ecosystem continues to expand, new technologies are addressing the requirements for managing, processing, analyzing, and storing data to help companies benefit from the rich sources of information flowing into their organizations. From NoSQL databases to open source projects to commercial products offered on-premises and in the cloud, the future of big data is being driven by innovative new approaches across the data management lifecycle. The most pressing areas include real-time data processing, interactive analysis, data integration, data governance, and security. Download this report for a better understanding of the current landscape, emerging best practices and real-world successes.
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evolution, big data, technology, datastax, nosql
    
Datastax
Published By: Microsoft     Published Date: Jul 20, 2018
At its Build conference in May, Microsoft took the wraps off Cosmos DB, the new incarnation of its existing cloud-based Azure DocumentDB NoSQL database. With a nod to the dramatic, Microsoft terms Cosmos DB as its biggest database bet since SQL Server; it is positioning it as its flagship cloud database, suited for use cases ranging from security and fraud detection, to IoT (consumer and industrial), personalization, e-commerce, gaming, social networks, chats, messaging, bots, oil and gas recovery and refining, and smart utility grids. Cosmos DB is a good example of how cloud platform providers are rethinking databases for scalable, elastic environments and commodity infrastructure. The platform that is most comparable is Google Cloud Spanner, but each of these databases is engineered for different purposes: Cosmos DB as a globally distributed operational database and Spanner as a globally distributed SQL-supporting OLTP database. The highlights of Cosmos DB include its flexibility in
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Microsoft
Published By: SnowFlake     Published Date: Jul 08, 2016
In the era of big data, enterprise data warehouse (EDW) technology continues to evolve as vendors focus on innovation and advanced features around in-memory, compression, security, and tighter integration with Hadoop, NoSQL, and cloud. Forrester identified the 10 most significant EDW software and services providers — Actian, Amazon Web Services (AWS), Hewlett Packard Enterprise (HPE), IBM, Microsoft, Oracle, Pivotal Software, SAP, Snowflake Computing, and Teradata — in the category and researched, analyzed, and scored them. This report details our findings about how well each vendor fulfills our criteria and where they stand in relation to each other to help enterprise architect professionals select the right solution to support their data warehouse platform.
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forrester, enterprise, data, technology, best practices, innovation, security, business technology
    
SnowFlake
Published By: Pentaho     Published Date: Jan 16, 2015
Download if you need to make decisions about the architecture of the systems you work on. Sponsored by Pentaho.
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embedded, big data, nosql, hadoop, customer analytics, data integration, data delivery, data management, data center
    
Pentaho
Published By: IBM     Published Date: May 02, 2014
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.
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ibm, big data, big sql, querying data, database management technology, apache hadoop, data administrators, infosphere, biginsights, industry-standard sql, management systems, database metadata, application programming interfaces, api, it management
    
IBM
Published By: IBM     Published Date: May 28, 2014
The ability to keep pace with trends like big data, open data, sophisticated analytics, and the de-compartmentalization of data silos and processes, distinguishes leading master data management (MDM) solutions from their counterparts. IBM, one of the five vendors in this evaluation, is positioned as THE leader with the most prominent, widely implemented solution in the market.
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ibm, forrester, master data management, big data, database management technology, data administrators, infosphere, biginsights, industry-standard sql, management systems, database metadata, application programming interfaces, api, data persistence, virtualize data, lifecycle management, big data strategy, it management, data management, data center
    
IBM
Published By: IBM     Published Date: Mar 05, 2014
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.
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ibm, big data, ibm big sql, sql, database management, database management technology, software, tables, queries, data platform, big sql architecture, programming language, relational database management system, rdbms, analytical applications, business intelligence, database development, data warehousing
    
IBM
Published By: Basho     Published Date: Apr 13, 2015
Today’s consumers expect instant access to communications services whether they’re in the office, at home, or on the road. With data speeds increasing and international roaming costs decreasing, data usage is rapidly growing. Telecommunications Service Providers (TSPs) are under pressure to deliver more services to more people and approach 100% uptime all while lowering prices to consumers. Traditional relational databases can’t meet the requirements for massive scalability, availability, and fault tolerance that the rapid growth in data usage and rise of big data demands. Read this solution brief to learn how Riak excels at these. Riak is a distributed NoSQL database optimized for big data. Riak meets many of the challenges you may be facing with your own service operations systems.
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riak, basho, telecommunications service provider, license fees, scalability, availability, data usage, big data, service operations system, networking, security, it management, wireless, data management
    
Basho
Published By: IBM     Published Date: Apr 29, 2015
IBM InfoSphere BigInsights for Hadoop enables organizations to efficiently manage and mine large volumes of diverse data for valuable insights. IBM builds on a 100% Apache Hadoop foundation with common tools such as spreadsheets, R analytics and SQL access for greater usability.
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bigsheets, data management, business intelligence, workload optimization, data, sql
    
IBM
Published By: HP     Published Date: Aug 26, 2014
HP Simply StoreIT takes the stress out of storage. HP and our network of over 200,000 channel partners worldwide can help you choose the right solutions to fit your biggest business challenges. We can help you overcome obstacles including too little time for managing IT, budgets for upgrading infrastructure, and too many business risks and threats. Now you can take charge of virtualization, storage for business solutions such as Exchange and SQL Server, growing file shares, and data protection for business continuity. Improve your operational efficiency, reduce your risks, and lower storage costs. See how.
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storage, budgets, server, virtualization, file, data, business, technology, portfolio, cloud-based, support, portal, solution, consolidate, islands, access, reliable, retention, protection, guesswork
    
HP
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