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Operational Database Offload
Operational Database Offload Partner Brief Facing increased data growth and cost pressures, scale‐out technology has become very popular as more businesses become frustrated with their costly “Our partnership with Hortonworks is able to scale‐up RDBMSs. With Hadoop emerging as the de facto scale‐out file system, a deliver to our clients 5‐10x faster performance Hadoop RDBMS is a natural choice to replace traditional relational databases and over 75% reduction in TCO over traditional scale‐up databases. With Splice like Oracle and IBM DB2, which struggle with cost or scaling issues. Machine’s SQL‐based transactional processing Designed to meet the needs of real‐time, data‐driven businesses, Splice engine, our clients are able to migrate their legacy database applications without Machine is the only Hadoop RDBMS. Splice Machine offers an ANSI‐SQL application rewrites” database with support for ACID transactions on the distributed computing Monte Zweben infrastructure of Hadoop. Like Oracle and MySQL, it is an operational database Chief Executive Office that can handle operational (OLTP) or analytical (OLAP) workloads, while scaling Splice Machine out cost‐effectively from terabytes to petabytes on inexpensive commodity servers. Splice Machine, a technology partner with Hortonworks, chose HBase and Hadoop as its scale‐out architecture because of their proven auto‐sharding, replication, and failover technology. This partnership now allows businesses the best of all worlds: a standard SQL database, the proven scale‐out of Hadoop, and the ability to leverage current staff, operations, and applications without specialized hardware or significant application modifications. What Business Challenges are Solved? Leverage Existing SQL Tools Cost Effective Scaling Real‐Time Updates Leveraging the proven SQL processing of Splice Machine leverages the proven Splice Machine provides full ACID Apache Derby, Splice Machine is a true ANSI auto‐sharding of HBase to scale with transactions across rows and tables by using SQL database on Hadoop. -
Of the Cloudtracker®
DIGITAL BANKS AND THE POWER OF THE CLOUD TRACKER® AUGUST 2020 How Holvi is Australian online-only Xinja Why the pandemic is pushing leveraging Kubernetes Bank turns to Kubernetes banks to go cloud-native for seamless service to enhance its mobile Page 8 banking features Page 19 FEATURE STORY Page 13 DEEP DIVE NEWS AND TRENDS TABLE OF CONTENTS 03 WHAT’S INSIDE Recent cloud and digital banking developments, such as why banks need to examine their container orchestration and Kubernetes investments as well as why the Royal Bank of Canada is employing AI and private cloud technology to accelerate its software innovation 08 FEATURE STORY An interview with Andrew Smith, director of technical operations for Finnish banking service Holvi, on why Kubernetes’ speed and scalability are essential to helping FIs swiftly deploy services for customers NEWS AND TRENDS 13 The latest cloud banking headlines, including why Australian business banking FinTech Tyro is using the cloud to upgrade its infrastructure and why Singapore’s Asia Digital Bank Corporation is leveraging the cloud to better contend for one of the region’s digital banking licenses DEEP DIVE 19 ACKNOWLEDGMENT An in-depth look at how the ongoing The Digital Banks And The Power Of The pandemic is pushing banks onto cloud-native ® Cloud Tracker was done in collaboration digital infrastructure and how systems like with NuoDB, and PYMNTS is grateful for the company’s support and insight. PYMNTS.com Kubernetes will prove essential for this move retains full editorial control over the following findings, methodology and data analysis. 23 ABOUT Information on PYMNTS.com and NuoDB WHAT’S INSIDE pproximately half a year has passed since the COVID-19 pandemic was declared and banks have largely determined how to continue their oper- ations as the industry faces significant challenges. -
Product 360: Retail and Consumer Industries
PRODUCT 360: RETAIL AND CONSUMER INDUSTRIES MARKLOGIC WHITE PAPER • NOVEMBER 2015 PRODUCT INFORMATION IS COMPLEX A major challenge for Retail and Consumer companies today is product proliferation and product complexity. An electronics retailer for example may have over 70,000 products in its catalog, while it is not uncommon for an industrial distributor to have over a million products and represent over 1,000 suppliers. Products HD typically have short shelf lives. In electronics for example it’s not uncommon for a new model to be released every year. And, a “Product” is not just a physical SKU (stock keeping unit) but a complex combination of structured HD and unstructured data that helps consumers search for, evaluate, compare, and choose their desired purchase. Product information includes a variety of data elements Product information includes a wide variety of data elements which are generated and stored in multiple locations, for example: WHY IS “PRODUCT 360” • Product descriptive information (e.g. size, color, IMPORTANT? material, nutritional information, usage, and other Creating, maintaining, and managing a 360 degree view elements that define it) of products is at the core of competitive differentiation • Digital images and videos – and in fact even survival – for retail and consumer • Customer ratings and reviews companies. • Dynamic pricing and promotions • Availability in-stock Key benefits of a Product 360 include: • Consumer loyalty information (who’s most likely to buy it) REVENUE GROWTH • Related products and accessories Today just 3% of on-line e-commerce transactions actually result in a sale. E-Commerce is the fastest These data elements often sit in different databases and growing channel for retailers, and sales via e-commerce legacy systems, making accessing them a challenge. -
Operational Database Overview Date Published: 2020-02-29 Date Modified: 2021-02-04
Cloudera Runtime 7.2.7 Operational Database Overview Date published: 2020-02-29 Date modified: 2021-02-04 https://docs.cloudera.com/ Legal Notice © Cloudera Inc. 2021. All rights reserved. The documentation is and contains Cloudera proprietary information protected by copyright and other intellectual property rights. No license under copyright or any other intellectual property right is granted herein. Copyright information for Cloudera software may be found within the documentation accompanying each component in a particular release. Cloudera software includes software from various open source or other third party projects, and may be released under the Apache Software License 2.0 (“ASLv2”), the Affero General Public License version 3 (AGPLv3), or other license terms. Other software included may be released under the terms of alternative open source licenses. Please review the license and notice files accompanying the software for additional licensing information. Please visit the Cloudera software product page for more information on Cloudera software. For more information on Cloudera support services, please visit either the Support or Sales page. Feel free to contact us directly to discuss your specific needs. Cloudera reserves the right to change any products at any time, and without notice. Cloudera assumes no responsibility nor liability arising from the use of products, except as expressly agreed to in writing by Cloudera. Cloudera, Cloudera Altus, HUE, Impala, Cloudera Impala, and other Cloudera marks are registered or unregistered trademarks in the United States and other countries. All other trademarks are the property of their respective owners. Disclaimer: EXCEPT AS EXPRESSLY PROVIDED IN A WRITTEN AGREEMENT WITH CLOUDERA, CLOUDERA DOES NOT MAKE NOR GIVE ANY REPRESENTATION, WARRANTY, NOR COVENANT OF ANY KIND, WHETHER EXPRESS OR IMPLIED, IN CONNECTION WITH CLOUDERA TECHNOLOGY OR RELATED SUPPORT PROVIDED IN CONNECTION THEREWITH. -
P6 Reporting Database Planning and Sizing
P6 Reporting Database Ver 3.0 Planning and Sizing An Oracle White Paper December 2011 Disclaimer The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle. Contents Introduction ...................................................................................................................................... 5 Critical Performance Factors ............................................................................................................ 5 Four Key Areas of the ETL ................................................................................................................. 6 Pulling Data between Servers ..................................................................................................... 6 Merging Updates into Target Database ...................................................................................... 6 PL/SQL-based Transformations .................................................................................................. 7 Planning Process .............................................................................................................................. 7 Why Planning is Key ......................................................................................................................... -
What Is Database? Types and Examples
What is database? Types and Examples Visit our site for more information: www.examplanning.com Facebook Page: https://www.facebook.com/examplanning10/ Twitter: https://twitter.com/examplanning10 TABLE OF CONTENTS Sr. Description 1 What is database? 2 Different definitions of database 3 Growth of Database 4 Elements of Database 5 Components of database 6 Database System Environment 7 Types of Databas 8 Characteristics of database 9 Advantages of Database 10 Disadvantages of Database What is Database? A database is a collection of information or data which are organized in such a way that it can be easily accessed, managed and retrieved. Database is abbreviated ad DB. Different definitions of database. “a usually large collection of data organized especially for rapid search and retrieval (as by a computer) an online database” (merriam-webster) “a comprehensive collection of related data organized for convenient access, generally in a computer.” (dictionary) A database is an organized collection of data. (Wikipedia) What is data? It is used as both singular and plural form. It can be a quantity, symbol or character on which operations are performed. Data is information which are converted into digital form. Growth of Database Database was evolved in 1960's started with the hierarchical database. Relational database was invented by EF Codd in 1970s while object oriented database was invented in 1980s. In 1990s object oriented database rose with the growth of object oriented programming languages. Nowadays, databases with SQL and NoSQL are popular. Elements of Database Database elements are fields, rows, columns, tables. All these are building blocks of database. -
Database Software Market: Billy Fitzsimmons +1 312 364 5112
Equity Research Technology, Media, & Communications | Enterprise and Cloud Infrastructure March 22, 2019 Industry Report Jason Ader +1 617 235 7519 [email protected] Database Software Market: Billy Fitzsimmons +1 312 364 5112 The Long-Awaited Shake-up [email protected] Naji +1 212 245 6508 [email protected] Please refer to important disclosures on pages 70 and 71. Analyst certification is on page 70. William Blair or an affiliate does and seeks to do business with companies covered in its research reports. As a result, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of this report. This report is not intended to provide personal investment advice. The opinions and recommendations here- in do not take into account individual client circumstances, objectives, or needs and are not intended as recommen- dations of particular securities, financial instruments, or strategies to particular clients. The recipient of this report must make its own independent decisions regarding any securities or financial instruments mentioned herein. William Blair Contents Key Findings ......................................................................................................................3 Introduction .......................................................................................................................5 Database Market History ...................................................................................................7 Market Definitions -
Data Platforms in Financial Services: the Nosql Edge
DATA PLATFORMS IN FINANCIAL SERVICES THE NOSQL EDGE WHITE PAPER Data Platforms in Financial Services: The NoSQL Edge Copying or distribution without written permission is prohibited 2 Contents Application and Criticality of Data Processing at Scale in Financial Services …………….. 06 • Fraud prevention, personalized customer experience, and risk management • Explosion of data sources, data sets, and formats • Shift from batch to near real-time to instantaneous • Growth of web-scale applications Common Challenges in Data Processing in Financial Services ………………………………….. 09 • Data silos caused by organizational structures • The increasing need for real-time processing • Always-on availability and performance • Consistency of data • Transition from mainframes to distributed workloads • Processing data for AI/ML in real-time Data Handling and Processing in Traditional Architectures ………………………………………. 12 • Not designed for extreme real-time workloads • Concentrates on data integrity over performance • Vertical scaling • Built for persistence and batch processing • Not in-memory • Slower response when implemented for real-time feedback • Caching layers built on top of operational layers NoSQL Databases in the Changing World of Financial Services …………………………..……. 15 • Digital transformation in financial services and the changes imposed by it • What is a NoSQL database? • Types of NoSQL databases • Growth of NoSQL databases Where NoSQL Databases Fit in Financial Services ……………………………………………………. 20 • NoSQL databases are better equipped to handle larger data sets • Ease of handling both structured and unstructured data formats • High-performance handling thereby designed for real-time feedback at web-scale • Built to connect legacy systems with newer and faster front-end systems • Built to drive two-paced development of modern architectures • Can scale better horizontally as the data grows • Easier and faster to implement compared to traditional databases • Support for better performance handling Opportunities and Business Benefits That Can Be Derived from NoSQL Databases ….. -
Leanxcale's Technology in a Nutshell
LeanXcale’s Technology in a Nutshell LeanXcale – technology is a nutshell 1 Gartner (HTAP), Forrester (translytical), LeanXcale technology in a and 451 research (HOAP). nutshell LeanXcale scales in all dimensions an enterprise needs: Introduction • Volume: to terabytes • Velocity: to 100s of millions of LeanXcale is a database designed for transactions per second fast-growing businesses and enterprise • Variety: natively supports SQL, companies who make intensive use of key-value, and soon JSON. It data. also supports polyglot queries across SQL and NoSQL (key- It is an ultra-scalable full SQL value data stores, graph operational database supporting full databases, document-oriented ACID transactions. It is possible thanks data stores, Hadoop data lakes) to a patented parallel-distributed and data streaming. transactional manager. It blends operational and analytical capabilities, enabling analytical queries over the operational data. All market analyst named this capability as the next future database technology: LeanXcale – technology is a nutshell 2 Architecture LeanXcale’s architecture has three distributed layers: Capacities LeanXcale was founded under the idea of the database technical excellence, trying to sort out all the problems that enterprise databases have. This philosophy is in the LeanXcale's DNA, and it is embodied in any database aspect, being the origin of more than ten disruptive technologies. • A distributed SQL query engine: It provides full SQL and a JDBC driver to access the database. It supports both scaling out OLTP workloads (distributing transactions across nodes) and OLAP workloads (using multiple nodes for a single large analytical query). Scalability • A distributed transaction Traditional ACID databases do not scale manager: It uses our patented out linearly or do not scale out at all. -
Supply 360: Retail & Consumer Industries
SUPPLY 360: RETAIL & CONSUMER INDUSTRIES MARKLOGIC WHITE PAPER • FEBRUARY 2016 The MarkLogic Supply 360 solution helps you better manage complexity, by providing a consolidated, operational view across the wide variety and sources of supply chain data – helping you grow revenue, manage risk and compliance, and address cost and operational concerns. MANAGING SUPPLY CHAIN COMPLEXITY A Supply Chain is a complex, dynamic environment. It connects all interactions from "Farm to Fork" in the Consumer Goods industry, and from the source of inputs or raw materials to the final point of sale at Retail. This process involves multiple players and the exchange of a wide variety of data across all the links in the supply chain – not only structured information but also unstructured documents including contracts, design objects, RFID sensors, carrier manifests, shipment notifications, and payments. The MarkLogic Supply 360 solution helps you better manage the complexity, by providing one consolidated view across the supply chain — design objects, bids and contracts, forecasts, inventory, procurement documents, and shipments. With MarkLogic, you can: Back-End Returns & Un-Saleables • Integrate and ingest multiple sources of data Figure 1: A simple version of a supply chain seamlessly into one operational database platform without upfront data modeling, saving you time and BENEFITS OF A SUPPLY 360 money Maintaining and managing a 360 degree view of your • Perform real-time search and query on all your data, supply chain and sources of supply delivers significant and get alerts on new items of importance benefits for consumer and retail companies. • Build applications to support forecasting, planning, GROW REVENUE and tracking especially for recalls and return of un- Plan and forecast the movement of products across saleables your supply chain and reduce out-of-stocks at retail. -
A New HOAP? Hybrid Operational- Analytic Processing and the Future
451 RESEARCH REPRINT REPORT REPRINT A new HOAP? Hybrid operational- analytic processing and the future of the database market MATT ASLETT, JAMES CURTIS 04 DEC 2017 Data from 451 Research’s Total Data Market Monitor indicates that databases designed to support a combination of operational and analytical processing workloads will quickly become mainstream, at least for new application projects. THIS REPORT, LICENSED TO MEMSQL, DEVELOPED AND AS PROVIDED BY 451 RESEARCH, LLC, WAS PUBLISHED AS PART OF OUR SYNDICATED MARKET INSIGHT SUBSCRIPTION SERVICE. IT SHALL BE OWNED IN ITS ENTIRETY BY 451 RESEARCH, LLC. THIS REPORT IS SOLELY INTENDED FOR USE BY THE RECIPIENT AND MAY NOT BE REPRODUCED OR RE-POSTED, IN WHOLE OR IN PART, BY THE RE- CIPIENT WITHOUT EXPRESS PERMISSION FROM 451 RESEARCH. ©2017 451 Research, LLC | WWW.451RESEARCH.COM 451 RESEARCH REPRINT 451 Research has previously identified the emergence of a new breed of database providers with products that are positioned for a combination of operational and analytical workloads, as well as the systems of intelligence workloads that they are used for. Data from 451 Research’s Total Data Market Monitor suggests that these databases that are designed to support hybrid operational and analytic processing (HOAP) will quickly become mainstream in the coming years – at least for new application projects. THE 451 TAKE The blending of operational and analytical systems continues to add value for many organizations. And while hybrid systems may not be an ideal fit for every firm, there are many reasons they do make sense. Beyond the reduction in maintaining a separate transactional and analytical system, hybrid databases enable organizations to carry out analytics on incoming operational data, taking advantage of the ‘transaction window,’ which, if done right, could be incredibly lucrative. -
Nuodb, a Peer to Peer Distributed Database for the Cloud
Research Seminar NuoDB, a peer to peer distributed database for the cloud Barry Morris Co-Founder & Chief Executive Officer, NuoDB Friday 19th June 2015 Abstract Traditionally, relational databases were designed for scale-up architectures. Supporting more clients or higher throughput required an upgrade to a larger server. Historically the alternatives for scale-out database management have been severely compromised, offering an unattractive choice between: a) Sacrificing transactional (ACID) guarantees (eg "NoSQL" approaches), b) Adopting tightly coupled models with significant flexibility and performance constraints (eg Shared disk or two-phase commit), or c) Application-specific data management (eg sharding). In the NewSQL model and in modern distributed datacenters, on-demand scale-out databases that maintain ACID semantics are an architectural requirement. Also critical are key features associated with being cloud-scale like ease of provisioning and management, security, agility in the face of unpredictable workloads or failures and support for widely distributed applications. Widely distributed applications, in turn, require distributed services that are highly available and can provide low latency. These are the design goals that defined the NuoDB architecture. NuoDB is a distributed database designed with global application deployment challenges in mind. It’s a true SQL service: all the properties of ACID transactions, standard SQL language support and relational logic. It’s also designed from the start as a distributed system that scales the way a cloud service has to scale providing high availability and resiliency with no single points of failure. Different from traditional shared-disk or shared-nothing architectures, NuoDB presents a new kind of peer-to-peer, on-demand independence that yields high availability, low-latency and a deployment model that is easy to manage.