Real-life DB2 tuning experİences with Apptune

Powering Microservices with MongoDB, Docker, Kubernetes & Kafka – MongoDB Eur...

Andrew Morgan

Organisations are building their applications around microservice architectures because of the flexibility, speed of delivery, and maintainability they deliver. Want to try out MongoDB on your laptop? Execute a single command and you have a lightweight, self-contained sandbox; another command removes all trace when you're done. Need an identical copy of your application stack in multiple environments? Build your own container image and then your entire development, test, operations, and support teams can launch an identical clone environment. Containers are revolutionizing the entire software lifecycle: from the earliest technical experiments and proofs of concept through development, test, deployment, and support. Orchestration tools manage how multiple containers are created, upgraded and made highly available. Orchestration also controls how containers are connected to build sophisticated applications from multiple, microservice containers. This presentation introduces you to technologies such as Docker, Kubernetes & Kafka which are driving the microservices revolution. Learn about containers and orchestration – and most importantly how to exploit them for stateful services such as MongoDB.

RedisConf17 - Searching Billions of Documents with Redis

Redis Labs

Redis Labs is a company that provides Redis Enterprise, a fully managed Redis database. Redis is an in-memory database but lacks search capabilities. Redis Labs developed RediSearch, a Redis module that allows for fast searching of billions of documents stored in Redis. RediSearch uses inverted indexes and custom data structures to enable full-text search, numeric filtering, and other search features in Redis in a memory-efficient way. It can also scale to handle large indexes by partitioning documents across multiple Redis servers and coordinating queries.

2-day-dba-oracle.pptx

Rocky572078

This document discusses migrating databases to Oracle's multitenant architecture. It begins with an overview of using AutoUpgrade to upgrade databases and then plugging them into a container database (CDB). It also covers concepts of Oracle Multitenant like pluggable databases (PDBs), resource sharing, and connecting to different containers. The document provides guidance on tasks like cloning PDBs, upgrading within a CDB, and migrating non-CDBs to PDBs.

Denver SQL Saturday The Next Frontier

The document discusses opportunities for using cloud and virtualization technologies. It describes how data virtualization can help optimize copy data management tasks like provisioning databases and refreshing environments. Virtualization allows creating many virtual copies of databases that take up minimal storage space since they share data blocks. This simplifies tasks like patching databases. The document also discusses best practices for migrating databases to the cloud and using data virtualization to enhance the migration process.

Cubrid - open source - 27mai2010

Catalin Ciobanu presented on CUBRID, an open source database management system. Some key points about CUBRID include that it is optimized for web services like click counters, supports high availability and unlimited storage, and provides high performance. It also has numerous applications for web development and allows for system maintenance without stopping services. Contact information was provided for sales, education, support, and marketing regarding CUBRID.

CUBRID DBMS presentation at Agora Open Source Conference

ArniaSoftware

Migration to Oracle Multitenant

Jitendra Singh

This document discusses upgrading to Oracle Database 19c and migrating to Oracle Multitenant. It provides an overview of key features such as being able to have 3 user-created PDBs without a Multitenant license in 19c. It also demonstrates how to use AutoUpgrade to perform an upgrade and migration to Multitenant with a single command. The document highlights various Multitenant concepts such as resource sharing, connecting to containers, and cloning PDBs.

Webinar: Simplifying the Database Experience with MongoDB Atlas

MongoDB

Running Kubernetes in Production: A Million Ways to Crash Your Cluster - Cont...

Henning Jacobs

Bootstrapping a Kubernetes cluster is easy, rolling it out to nearly 200 engineering teams and operating it at scale is a challenge. In this talk, we are presenting our approach to Kubernetes provisioning on AWS, operations and developer experience for our growing Zalando developer base. We will walk you through our horror stories of operating 80+ clusters and share the insights we gained from incidents, failures, user reports and general observations. Most of our learnings apply to other Kubernetes infrastructures (EKS, GKE, ..) as well. This talk strives to reduce the audience’s unknown unknowns about running Kubernetes in production. https://2018.container.camp/uk/schedule/running-kubernetes-in-production-a-million-ways-to-crash-your-cluster/

Cubrid - Open Source DBMS highly optimized for Web Applications

The document discusses CUBRID, an open source database management system. CUBRID is optimized for web services like click counters and is designed for high performance, high availability, and unlimited storage. It also supports various programming languages and has free tools for installation, management and development. Contact information is provided for sales, education, support and marketing of CUBRID.

RMOUG 18 - Winning Performance Challenges in Oracle Multitenant

This document discusses winning performance challenges in Oracle Multitenant environments. It begins with introducing the speaker, Pini Dibask, who is a Product Manager for Database Tools at Quest Software. It then provides an overview of Quest Software and their database management solutions. The remainder of the document outlines the agenda, which includes introductions to database consolidation, Oracle Multitenant concepts, ensuring quality of service in multitenant environments, RAC and multitenancy, and performance monitoring for multitenant environments.

Making your Life Easier with MongoDB and Kafka (Robert Walters, MongoDB) Kafk...

HostedbyConfluent

Kafka Connect makes it possible to easily integrate data sources like MongoDB! In this session we will first explore how MongoDB enables developers to rapidly innovate through the use of the document model. We will then put the document model to life and showcase how to integrate MongoDB and Kafka through the use of the MongoDB Connector with Apache Kafka. Finally, we will explore the different ways of using the connector including the new Confluent Cloud integration.

Understanding IBM Tivoli OMEGAMON for DB2 Batch Reporting, Customization and ...

This document discusses tuning IBM Tivoli OMEGAMON for DB2 Batch Reporting, Customization, and Tuning Practices. It outlines the general tuning process including application performance, database design, DB2 subsystem, and other factors. It then discusses options for tuning including manual methods using tools like Explain or DB2 commands, or automated tools like Omegamon. Finally, it provides details on DB2 system and application monitoring including online monitoring, batch reporting, DB2 traces, SMF configuration, and reporting structures.

SQL Server 2019 Big Data Cluster

Maximiliano Accotto

Winning Performance Challenges in Oracle Multitenant

Pini Dibask, a senior product manager at Quest Software, gave a presentation on winning performance challenges in Oracle Multitenant. The presentation covered Oracle Multitenant concepts, ensuring quality of service in multitenant environments through resource management, using RAC with multitenant, and performance monitoring tools. It discussed how Oracle Resource Manager can be used to allocate resources between pluggable databases at the container database level. The presentation also showed how tools from Quest such as Foglight can provide performance monitoring across multiple databases.

How to build a social network on serverless

Yan Cui

Many people are building different workloads using serverless technologies these days, but how would a non-trivial system such as a social network look like on serverless? In this talk Yan will discuss his journey of migrating a social network startup to serverless, and how his team was able to improve performance, scalability and feature delivery using serverless technologies. Yan will discuss how serverless technologies such as Lambda are used to implement each part of their system, including search, push notifications, timeline, user recommendations, and business intelligence. If you're wondering how serverless can be used to solve a wide variety of challenges in your business, this is the talk for you.

Under the Hood - Couchbase Server Architecture - June 2015

Cihan Biyikoglu

Home Office

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DB2 Real-Time Analytics Meeting Wayne, PA 2015 - IDAA & DB2 Tools Update

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DB2 Real-Time Analytics Meeting Wayne, PA 2015 - IDAA & DB2 Tools Update

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Cubrid - Open Source DBMS highly optimized for Web Applications

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More from Cuneyt Goksu

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Db2 for z os trends

This document summarizes a presentation about trends and directions for Db2 for z/OS. It discusses Db2 for z/OS's strategy of investing in AI, cloud, and analytics while simplifying and modernizing. It provides an overview of recent releases of Db2 12 including new features and function levels delivered through continuous delivery. It also discusses future potential features such as Db2 AI for z/OS and integration with IBM Cloud Pak for Data.

Db2 analytics accelerator technical update

This document provides an overview and update on Db2 Analytics Accelerator. It discusses the Accelerator's version 7.5 functionality including integrated synchronization, a wider range of scalability, and pass-through support for additional built-in functions. It also reviews the Accelerator's deployment options and data synchronization techniques for incremental updates with low latency between Db2 for z/OS and the Accelerator.

Perfect trio : temporal tables, transparent archiving in db2 for z_os and idaa

Temporal tables and transparent archiving in DB2 for z/OS, combined with IDAA, provide three key benefits: 1. They allow organizations to retain data for long periods of time in a cost-effective manner by moving inactive data offline. 2. They improve application performance by separating newer, more frequently accessed rows from older, less frequently accessed rows. 3. They enable transparent access to both current and archived data through a single query, reducing the need for application changes.

How should I monitor my idaa

This document discusses how to monitor an IBM Db2 Analytics Accelerator (IDAA). It provides an overview of the resources, use cases, and tools for monitoring an IDAA. Key metrics for monitoring include accelerator resources, system resources, SQL statements, workload, performance, and capacity planning. Tools mentioned for monitoring include the appliance UI, OMPE, Data Studio, DISPLAY ACCEL command, and stored procedures.

Ibm machine learning for z os

IBM z Analytics provides machine learning capabilities for enterprise data on IBM Z mainframes. The presentation discusses machine learning concepts and how IBM solutions apply machine learning to real-world problems. It demonstrates how to build machine learning models using Spark on transactional data from IBM Z, and how trained models can be deployed on IBM Z to power applications in real-time. IBM offers multiple options for machine learning including on cloud, on-premises, and optimized for IBM Z to best suit enterprise needs.

Machine Learning for z/OS

IBM's zAnalytics strategy provides a complete picture of analytics on the mainframe using DB2, the DB2 Analytics Accelerator, and Watson Machine Learning for System z. The presentation discusses updates to DB2 for z/OS including agile partition technology, in-memory processing, and RESTful APIs. It also reviews how the DB2 Analytics Accelerator can integrate with Machine Learning for z/OS to enable scoring of machine learning models directly on the mainframe for both small and large datasets.

Temporal Tables, Transparent Archiving in DB2 for z/OS and IDAA

The document discusses several data archiving solutions for z/OS systems including temporal tables, transparent archiving, and IDAA technology. Temporal tables allow querying and updating historical data using system time periods. Transparent archiving moves old data to other storage platforms while still allowing dynamic queries. IDAA provides accelerated query performance for temporal tables by routing queries to an accelerator system. The solutions can be combined for different use cases depending on data retention and access needs.

IDUG NA 2014 / 11 tips for DB2 11 for z/OS

DB2 11 includes several new features such as global variables, the ability to alter partition keys online without impacting availability, selecting data from directory tables, dropping columns, auto-mapping of tables during reorganization, transparent archiving of data, enhancements to RUNSTATS utilities, and deprecated functionality. Some highlights include global variables that can be shared across SQL statements, altering partition limits online which sets partitions to AREOR status until reorganization, and dropping columns in tables without taking them offline.

Seçsi̇s sistemi hakkında değerlendirme ve önerilerCuneyt Goksu

Gaining Insight into

This technical white paper discusses using SQL performance reports to understand stored procedure characteristics in DB2. The paper explains how to identify if a stored procedure is running externally or internally using the program type and stored procedure address space details. It also shows how to determine what program or plan is calling the stored procedure using the plan drilldown. The paper emphasizes the importance of understanding where stored procedures are executing from and the application environment, for effective performance tuning.

Identify SQL Tuning Opportunities

This technical white paper discusses using SQL performance analysis to identify tuning opportunities in DB2. It outlines how the Object Analysis report in APPTUNE for DB2 can help by showing the most used databases, tables, programs, and SQL statements. The paper then walks through an example where tuning the most frequent SQL statement on the most accessed table, which was executing millions of times, helped reduce the number of getpages and improve overall system performance.

Diagnose RIDPool Failures

The document discusses identifying tablespace scans caused by RID list failures in DB2. It provides an example where a SQL statement with a high getpage count was found to have 210 RID list failures, resulting in 210 tablespace scans. Analyzing dynamic statement cache statistics and execution statistics at the statement level can help identify when an access path is converted to a tablespace scan due to RID pool failures. Adjusting related RID pool DSNPARM settings or reducing dependence on the RID pool may help address the issue.

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Denver 2012 -- After IDUG Conference

Pete and I spent 4 days exploring Colorado in an RV after an IDUG conference in Denver. We camped at Echo Lake Park and saw snow in May, hiked cliffs and watched people jump, visited the Royal Gorge Bridge, stayed overnight between the Rocky Mountains, saw sand dunes at Great Sand Dunes National Park, explored wildlife refuges with many birds and animals, and drove through canyons shooting scenic photos before returning to Denver.

BIG DATA Nedir ve IBM Çözümleri.

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