Red hatpartner2013edb futureofdatabase

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Our own Sean Doherty was in Madrid this week, presenting at the Red Hat Partner summit on the rise of big data and what it means for the future of the RDBMS in the enterprise. Check out his presentation!

The Future of Database for the Enterprise
Sean Doherty
Vice president, Business Development and International Sales
sean@enterprisedb.com
October, 2013

Session title
The Future of Database for the Enterprise Non -confidential 2
Agenda
!  Today's World of Data
!  Database Choices
!  What's In Store for Enterprise Data and Database Needs?
!  Effect on Partners
!  Questions

Session title
The Future of Database for the Enterprise Non -confidential 3
Dang, that’s a lot of data!
90% of the data in the world today was created in the last two years.
x
VALUE

Session title
The Future of Database for the Enterprise Non -confidential 4
What is Big Data?
!  Volume—There's a lot of it
!  Variety—It comes from many (disparate) sources
!  Velocity—It's produced very quickly
!  Variability—Potential inconsistencies
!  Complexity—Linking, connecting, correlating, i.e.
manageability
!  Structured? Unstructured? Schemas? Schema-less?
!  Most data is 'unstructured'—no latent meaning
!  BUT, it's still stored in a 'structured' way....just differently

Session title
The Future of Database for the Enterprise Non -confidential 5
NoSQL Options—Schema-less Database Hell!
!  MongoDB
!  What you'd use MySQL for, but you don't
want pre-defined columns
!  CouchDB
!  Accumulating (and occasionally changing)
data—CRM, CMS
!  Hbase
!  Billions of rows, millions of tables—search
engines
!  Cassandra
!  Fast columner querying, writes faster than
reads, not for transactions—data analytics
!  Riak
!  Point-of-sales data collection
!  Redis
!  Rapidly changing data—stock prices,
analytics
!  Hypertable
!  A faster, smaller Hbase
!  VoltDB
!  Acting fast on vast amounts of incoming data
—point of sales data analytics
!  Neo4j
!  Route searching and technologies
...and there are many, many more!

Session title
The Future of Database for the Enterprise Non -confidential 6
Current & Future Size of Database Market
For commercial, paid use,
relational database is still
the target

Session title
The Future of Database for the Enterprise Non -confidential 7
Who Owns the Enterprise Database Market?

Session title
The Future of Database for the Enterprise Non -confidential 8
The 80's Are In!

Session title
The Future of Database for the Enterprise Non -confidential 9
The 80's Are In!
PostgreSQL—The World's Most Advanced Open
Source Database
Fully ACID Compliant
MVCC
Point in Time Recovery (PITR)‫‏‬
Data and Index Partitioning
Bitmap Indexes
ANSI Constraints
Triggers & Stored Functions
Views & Data Types
Nested Transactions
Online Backup
Online Reorganization
Foreign Keys
Streaming Replication
Multi-Core Support

Session title
The Future of Database for the Enterprise Non -confidential 10
How RDBMS’s and Postgres Have Evolved
!  Object Relational Database Features in the '90s
!  XML Storage Capabilities at the turn of the century
!  NoSQL & 'non-standard' SQL Features
!  JSON
!  Non-durable Storage
!  PostgreSQL's hstore
!  PLV8
!  Full Text Indexing
!  PPAS Connector for Hadoop
!  PPCD's Ability to Add Databases
!  Oracle Database Compatibility

Session title
The Future of Database for the Enterprise Non -confidential 11
Postgres At A Tipping Point
!  Proven track record
!  Budgetary constraints
!  Use by massive companies &
governments
!  Staggering cost savings
!  Major advances in the core
technology
!  Acceptance and widespread
adoption of open source software
!  Platform shift
!  Global commercial entity
spearheading with large
ecosystem of partners

Session title
The Future of Database for the Enterprise Non -confidential 12
Enabling Commercial Adoption of Postgres
Data Integration Requires the Proper Database Foundation

Session title
The Future of Database for the Enterprise Non -confidential 13
Where Do We Fit?
Hadoop!
NoSQL!

Session title
The Future of Database for the Enterprise Non -confidential 14
Partnering With EnterpriseDB
!  EMEA—our fastest growing region
!  Doubled our staff
!  Annuity-based sale
!  New services revenue streams
!  COGS reduction means margin increases
!  Growing ecosystem to take advantage of
!  Local language support
!  Local services needed
!  The move is happening now—join us!

Gary Carter, Director of Product Marketing presents the accelerating adoption of Postgres by large organizations interested in reducing their database costs. He reviews the main drivers of Postgres adoption, as well as the profiles of several organizations currently reaping the benefits of Postgres, and explore a few strategies that your organization can leverage to make the move at your pace – quickly or slowly. To see the Webcast recording – please visit EnterpriseDB > Resources > Webcasts. Questions? Contact sales@enterprisedb.com

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"Why use PgBouncer? It’s a lightweight, easy to configure connection pooler and it does one job well. As you’d expect from a talk on connection pooling, we’ll give a brief summary of connection pooling and why it increases efficiency. We’ll look at when not to use connection pooling, and we’ll demonstrate how to configure PgBouncer and how it works. But. Did you know you can also do this? 1. Scaling PgBouncer PgBouncer is single threaded which means a single instance of PgBouncer isn’t going to do you much good on a multi-threaded and/or multi-CPU machine. We’ll show you how to add more PgBouncer instances so you can use more than one thread for easy scaling. 2. Read-write / read only routing Using different pgBouncer databases you can route read-write traffic to the primary database and route read-only traffic to a number of standby databases. 3. Load balancing When we use multiple PgBouncer instances, load balancing comes for free. Load balancing can be directed to different standbys, and weighted according to ratios of load. 4. Silent failover You can perform silent failover during promotion of a new primary (assuming you have a VIP/DNS etc that always points to the primary). 5. And even: DoS prevention and protection from “badly behaved” applications! By using distinct port numbers you can provide database connections which deal with sudden bursts of incoming traffic in very different ways, which can help prevent the database from becoming swamped during high activity periods. You should leave the presentation wondering if there is anything PgBouncer can’t do."

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In this talk I'll discuss how we can combine the power of PostgreSQL with TensorFlow to perform data analysis. By using the pl/python3 procedural language we can integrate machine learning libraries such as TensorFlow with PostgreSQL, opening the door for powerful data analytics combining SQL with AI. Typical use-cases might involve regression analysis to find relationships in an existing dataset and to predict results based on new inputs, or to analyse time series data and extrapolate future data taking into account general trends and seasonal variability whilst ignoring noise. Python is an ideal language for building custom systems to do this kind of work as it gives us access to a rich ecosystem of libraries such as Pandas and Numpy, in addition to TensorFlow itself.

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Has your table become too large to handle? Have you thought about chopping it up into smaller pieces that are easier to query and maintain? What if it's in constant use? An introduction to the problems that can arise and how PostgreSQL's partitioning features can help, followed by a real-world scenario of partitioning an existing huge table on a live system. We will be looking at the problems caused by having very large tables in your database and how declarative table partitioning in Postgres can help. Also, how to perform dimensioning before but also after creating huge tables, partitioning key selection, the importance of upgrading to get the latest Postgres features and finally we will dive into a real-world scenario of having to partition an existing huge table in use on a production system.

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There have been plenty of “explaining EXPLAIN” type talks over the years, which provide a great introduction to it. They often also cover how to identify a few of the more common issues through it. EXPLAIN is a deep topic though, and to do a good introduction talk, you have to skip over a lot of the tricky bits. As such, this talk will not be a good introduction to EXPLAIN, but instead a deeper dive into some of the things most don’t cover. The idea is to start with some of the more complex and unintuitive calculations needed to work out the relationships between operations, rows, threads, loops, timings, buffers, CTEs and subplans. Most popular tools handle at least several of these well, but there are cases where they don’t that are worth being conscious of and alert to. For example, we’ll have a look at whether certain numbers are averaged per-loop or per-thread, or both. We’ll also cover a resulting rounding issue or two to be on the lookout for. Finally, some per-operation timing quirks are worth looking out for where CTEs and subqueries are concerned, for example CTEs that are referenced more than once. As time allows, we can also look at a few rarer issues that can be spotted via EXPLAIN, as well as a few more gotchas that we’ve picked up along the way. This includes things like spotting when the query is JIT, planning, or trigger time dominated, spotting the signs of table and index bloat, issues like lossy bitmap scans or index-only scans fetching from the heap, as well as some things to be aware of when using auto_explain.

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EDB

Internet of Things is a currently a burgeoning market, and is often associated with specialized data-stores. However PostgreSQL is just as capable at this use-case and can offer some compelling advantages. We’ll explore ways to store IoT data in PostgreSQL covering various ways to store and structure this kind of data. How range types and differing types of indexes can be of use. Also taking a quick look at some extensions designed for this use case. Then looking at powerful SQL features which can really help when analyzing IoT data streams, and how the power of a real SQL database can be a key advantage.

A Journey from Oracle to PostgreSQL

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I would like you to join me on our journey from a complex, multi instance Oracle topology to a single logical database in PostgreSQL. Each technology and architectural decision point will be discussed describing how we arrived at our destination. There are five keys areas that will be covered: - Target architecture - Migration of database objects (tables, indexes, views, synonyms, etc) - Migration of database code (packages, functions, procedures, triggers) - Application tier - Migration of Data - with minimal downtime during cutover The target architecture is a BDR cluster, where the physical data model and data stored is different between the logical standbys and the lead master/shadow master. Will discuss how this allowed for the simplification of the topology, and the benefits this delivered. Before you go there, yes I know PostgreSQL does no have synonyms, but an alternative approach was needed. There is a significant amount of business logic in the database tier all of which needed to be translated into database code. Will look at the tools and extensions available to reproduce the functionality in PostgreSQL. Look at common non-ISO standard SQL embedded in the application tier, along with jdbc challenges. Finally a look at some of the data movement tools available. Full disclosure, we are still on the journey but have learnt a lot on the way.

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The proposed talk will go through several questions. The first obvious one is why would I bother learn CLI when I can do whatever I need with a GUI tool? We'll try to answer why knowing CLI is a MUST for some people (like Postgres DBAs, for example) whereas it's only a bonus for others (like data scientists, for example). Then we'll go through the basics about 101 (how to connect to, interactive mode versus not interactive more, how to set psql environment to work comfortably and so on...) The last part will be about tips and tricks that will make anyone's journey with psql more effective and enjoyable. I'm looking for the "TIL" effect in people's eyes.

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Cloud Native PostgreSQL - Italiano

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Vieni a scoprire Cloud Native PostgreSQL (CNP), l’operatore per Kubernetes, direttamente da coloro che lo hanno ideato e lo sviluppano in EDB. CNP facilita l’integrazione di database PostgreSQL con le tue applicazioni all’interno di cluster Kubernetes e OpenShift Container Platform di RedHat, grazie alla sua gestione automatica dell’architettura primario/standby che include: self-healing, failover, switchover, rolling update, backup, ecc. Durante il webinar affronteremo i seguenti punti: - DevOps e Cloud Native - Introduzione a Cloud Native PostgreSQL - Architetture - Caratteristiche principali - Esempi di uso e configurazione - Kubernetes, Storage e Postgres - Demo - Conclusioni

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EDB 13 enhances our flagship database server and tools. This webinar will explore its security, usability, and portability updates. Join us to learn how EDB 13 can help you improve your PostgreSQL productivity and data protection. Webinar highlights include: - New security features such as SCRAM and the encryption of database passwords and traffic between Failover Manager agents - Usability updates that automate partitioning, verify backup integrity and streamline the management of failover and backups - Portability improvements that simplify running PostgreSQL across on-premise and cloud environments

Cloud Native PostgreSQL - APJ

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EDB Cloud Native Postgres includes database container images and a Kubernetes Operator that manage the lifecycle of a database from deployment to operations. This Kubernetes Operator for Postgres is written by EDB entirely from scratch in the Go language and relies exclusively on the Kubernetes API. Attend this webinar to learn about: - DevOps & Cloud Native - Overview of Cloud Native Postgres - Storage for Postgres workloads in Kubernetes - Using Cloud Native Postgres - Demo

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1. The Future of Database for the Enterprise Sean Doherty Vice president, Business Development and International Sales sean@enterprisedb.com October, 2013

2. Session title The Future of Database for the Enterprise Non -confidential 2 Agenda !  Today's World of Data !  Database Choices !  What's In Store for Enterprise Data and Database Needs? !  Effect on Partners !  Questions

3. Session title The Future of Database for the Enterprise Non -confidential 3 Dang, that’s a lot of data! 90% of the data in the world today was created in the last two years. x VALUE

4. Session title The Future of Database for the Enterprise Non -confidential 4 What is Big Data? !  Volume—There's a lot of it !  Variety—It comes from many (disparate) sources !  Velocity—It's produced very quickly !  Variability—Potential inconsistencies !  Complexity—Linking, connecting, correlating, i.e. manageability !  Structured? Unstructured? Schemas? Schema-less? !  Most data is 'unstructured'—no latent meaning !  BUT, it's still stored in a 'structured' way....just differently

5. Session title The Future of Database for the Enterprise Non -confidential 5 NoSQL Options—Schema-less Database Hell! !  MongoDB !  What you'd use MySQL for, but you don't want pre-defined columns !  CouchDB !  Accumulating (and occasionally changing) data—CRM, CMS !  Hbase !  Billions of rows, millions of tables—search engines !  Cassandra !  Fast columner querying, writes faster than reads, not for transactions—data analytics !  Riak !  Point-of-sales data collection !  Redis !  Rapidly changing data—stock prices, analytics !  Hypertable !  A faster, smaller Hbase !  VoltDB !  Acting fast on vast amounts of incoming data —point of sales data analytics !  Neo4j !  Route searching and technologies ...and there are many, many more!

6. Session title The Future of Database for the Enterprise Non -confidential 6 Current & Future Size of Database Market For commercial, paid use, relational database is still the target

7. Session title The Future of Database for the Enterprise Non -confidential 7 Who Owns the Enterprise Database Market?

8. Session title The Future of Database for the Enterprise Non -confidential 8 The 80's Are In!

9. Session title The Future of Database for the Enterprise Non -confidential 9 The 80's Are In! PostgreSQL—The World's Most Advanced Open Source Database Fully ACID Compliant MVCC Point in Time Recovery (PITR)‫‏‬ Data and Index Partitioning Bitmap Indexes ANSI Constraints Triggers & Stored Functions Views & Data Types Nested Transactions Online Backup Online Reorganization Foreign Keys Streaming Replication Multi-Core Support

10. Session title The Future of Database for the Enterprise Non -confidential 10 How RDBMS’s and Postgres Have Evolved !  Object Relational Database Features in the '90s !  XML Storage Capabilities at the turn of the century !  NoSQL & 'non-standard' SQL Features !  JSON !  Non-durable Storage !  PostgreSQL's hstore !  PLV8 !  Full Text Indexing !  PPAS Connector for Hadoop !  PPCD's Ability to Add Databases !  Oracle Database Compatibility

11. Session title The Future of Database for the Enterprise Non -confidential 11 Postgres At A Tipping Point !  Proven track record !  Budgetary constraints !  Use by massive companies & governments !  Staggering cost savings !  Major advances in the core technology !  Acceptance and widespread adoption of open source software !  Platform shift !  Global commercial entity spearheading with large ecosystem of partners

12. Session title The Future of Database for the Enterprise Non -confidential 12 Enabling Commercial Adoption of Postgres Data Integration Requires the Proper Database Foundation

13. Session title The Future of Database for the Enterprise Non -confidential 13 Where Do We Fit? Hadoop! NoSQL!

14. Session title The Future of Database for the Enterprise Non -confidential 14 Partnering With EnterpriseDB !  EMEA—our fastest growing region !  Doubled our staff !  Annuity-based sale !  New services revenue streams !  COGS reduction means margin increases !  Growing ecosystem to take advantage of !  Local language support !  Local services needed !  The move is happening now—join us!

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