OpenWorks

February 25-27, 2019 - New York

Agenda Highlights

Workshops

Deep dive into specific technical topics – sign up early as workshops fill fast!

Keynotes

Hear about what’s next – vision, roadmap, and how MariaDB will solve tomorrow’s problems.

Sessions

Learn from peers and experts from different industries on how MariaDB has delivered significant business value.

Background Divider Element

WORKSHOP OVERVIEW

  • High availability

    Get an in-depth overview of the high availability (HA) options for MariaDB TX in this workshop, from aysnchronous and semi-synchronous replication with automatic failover to synchronous clustering, and gain hands-on experience setting up and testing different HA configurations.

  • Advanced security

    Gain hands-on experience securing MariaDB TX deployments – all the way from initial installation to advanced security configuration and tactics such as data-at-rest encryption, pluggable authentication, query blocking, data masking and more. MariaDB experts will be on hand to guide workshop attendees throughout the process, ensuring everyone leaves ready to manage MariaDB TX in secure environments.

  • Performance tuning

    Discover best practices and tips for maximizing the performance of MariaDB TX in this workshop, where MariaDB’s Remote DBA team will highlight important configuration parameters and share how to optimize everything from queries and indexes to storage and replication through a series of hands-on exercises.

  • Modern analytics

    Learn how distributed, columnar storage and massively parallel processing (MPP) work in this MariaDB AX workshop, where MariaDB engineers will explain the architecture of MariaDB AX and walk attendees through installation, data loading and querying with built-in functions and distributed user-defined functions.

Agenda Track Descriptions and Sessions

  • Real-world case studies

    MariaDB customers will share business and technical database requirements and why they chose to standardize on MariaDB, current and future use cases, what they learned after migrating from a proprietary database, how they run on container infrastructure and their overall experience with MariaDB thus far.

    Click ‘See More’ to view sessions in this track

    See More

    How THINQ runs both transactions and analytics at scale

    THINQ provides a cloud-based Communications-Platform-as-a-Service (CPaaS) that routes tens of millions of phone calls per day for customers in enterprise and telecommunications industries. We’ll explain how we combined MariaDB Server and MariaDB ColumnStore to support both high-performance transaction processing and scalable analytics. In addition, we’ll share some of our best practices and lessons learned from supporting an ever-increasing database workload that currently exceeds 10,000 transactions per second, including:

    – Improving resilience by automating failover with MariaDB clustering
    – Lowering deadlock frequency through an open-source client-side solution
    – Streaming critical data to MariaDB ColumnStore for near real-time analytics
    – Achieving critical data redundancy with ColumnStore transactions
    – Evaluating geo-distributed MariaDB ColumnStore cluster and the bulk write SDK

    _______________

    How QBerg scaled to store data longer, query it faster

    The continuous increase in terms of services and countries to which QBerg delivers its services requires an ever-increasing load of resources. During the last year QBerg has reached a critical point, storing so much transactional data that standard relational databases were unable to meet the SLAs, or support the features, required by customers. As an example, we had to cap web analytics to running on a maximum of four months of history. The introduction of MariaDB Columnstore, flanked by existing MariaDB Server databases, not only will allow us to store multiple years’ worth of historical data for analytics – it decreased overall processing time by one order of magnitude right off the bat. The move to a unified platform was incremental, using MariaDB MaxScale as both a router and a replicator. We are now able to replicate full InnoDB schemas to MariaDB ColumnStore and incrementally update big tables without impacting the performance of ongoing transactions.
    _______________

    Check back soon for more sessions offered in this track!

  • Product internals and roadmap

    MariaDB engineers will go under the hood to explain how things like Oracle Database compatibility and different storage engines work while MariaDB product managers will provide an overview of the next release and an update on strategic initiatives, including DBaaS, machine learning and MariaDB Manager.

    Click ‘See More’ to view sessions in this track

    See More

    What’s new in the world of MariaDB

    In this session, we’ll provide a quick overview of the new features in MariaDB Server 10.3 and MariaDB MaxScale 2.3 before turning our focus to what’s new in MariaDB Server 10.4, including instant DROP COLUMN, the INTERVAL data type and advanced security features like denial of service and password crack detection.
    _______________

    Migrating from InnoDB and HBase to MyRocks at Facebook

    Facebook created a new storage engine called MyRocks to optimize space and write performance, and recently migrated both UDB (a database for social activities, and our biggest in production) and Facebook Messenger to MyRocks. In this session, Yoshinori Matsunobu of Facebook will talk about the challenges, benefits and lessons learned by migrating these applications from InnoDB to MyRocks.
    _______________

    What’s new in Galera 4

    MariaDB Server 10.4 will introduce Galera 5. This presentation will give an overview of the new features coming with Galera 4 replication, such as:

    – Large transactions with streaming replication
    – Non-blocking DDL schema changes having less impact on the cluster
    – Emergency aborts being handled with a voting protocol to minimize aborts
    – End-to-end encrypted replication
    – Support for XA transactions

    The presentation will also show how Galera 4 will affect application use in terms of cluster configuration, upgrade procedures and new use cases for MariaDB Server 10.4.
    _______________

    Query optimizer: further down the rabbit hole

    There were a number of improvements to the query optimizer in MariaDB Server 10.3, and even more are coming in MariaDB Server 10.4. We will start with a technical introduction of how the query optimizer works in MariaDB Server, provide technical explanations of recent query optimizations (including semi-join optimizations for single-table UPDATE/DELETE queries and condition pushdown with PARTITION BY) and discuss future improvements.
    _______________

    Separating analytical queries to improve performance

    In order to meet the growing analytical requirements of data-driven organizations (more data, faster responses), MariaDB Server can use MariaDB ColumnStore to offload historical data and analytical queries. In this session, we’ll show how change-data-capture and query routing, both available out of the box, can be used to scale analytics without changing application code or deploying a data warehouse.
    _______________

    Oracle Database compatibility: phase II

    Oracle Database compatibility, introduced in MariaDB Server 10.3, is being expanded in MariaDB Server 10.4. In this session, we’ll explain how Oracle Database compatibility was implemented, what syntax and features are supported today and which ones will be added to the next release.
    _______________

    How MariaDB is approaching DBaaS

    In last year’s keynote MariaDB CEO Michael Howard announced an initiative to build a MariaDB DBaaS platform. This year the DBaaS team will share how they are approaching DBaaS, and discuss the role of containers and Kubernetes, the need for infrastructure-agnostic provisioning, support for day two operations and enterprise requirements for large-scale DBaaS deployments.
    _______________

    Using machine learning to improve quality of service

    MariaDB Labs was started to advance database research in multiple areas, including the application of machine learning to continuously improve database performance, efficiency and security. Now the machine learning team at MariaDB is ready to share the preliminary results of their work – using machine learning to maintain or improve SLAs by proactively identifying areas of further optimization in MariaDB Server.
    _______________

    ClustrixDB: how distributed databases scale out

    ClustrixDB, now part of MariaDB, is a fully distributed and transactional RDBMS for applications with the highest scalability requirements. In this session, the VP of Engineering for ClustrixDB will provide an introduction to ClustrixDB, followed by an in-depth technical overview of its architecture, with a focus on distributed storage, transactions and query processing – and its unique approach to index partitioning.
    _______________

    Eliminating table rebuilds for instant schema changes

    MariaDB Server 10.3 introduced ALGORITHM=NOCOPY, allowing columns to be added in an instant because adding columns no longer required rebuilding a table. In MariaDB Server 10.4, we’re taking this a step further with instant DROP COLUMN and instant ALTER TABLE to support many more instant schema changes. In this session, we’ll explain how instant schema changes work and how we’re eliminating table rebuilds.
    _______________

    Removing locks for faster backups in MariaDB Server 10.4

    In this session, we’ll explain how we reduced the number of locks needed for backups by creating the BACKUP LOCK syntax as a more efficient alternative to FLUSH TABLE WITH READ LOCK – and for all storage engines with local, persistent storage. We’ll walk through the process step-by-step and explain each stage of the backup process to indicate where locking has been removed or the scope narrowed.
    _______________

    Transparent sharding with Spider: going vertical

    MariaDB Server 10.3 introduced transparent, built-in sharding with the Spider storage engine to scale out reads, writes and storage. MariaDB Server 10.4 includes a number of improvements, including vertical partitioning. In this session, we’ll show how to set up a sharded MariaDB cluster and scale out on demand, as well explore as best practices for high availability and consistency in a sharded deployment.
    _______________

  • Operations and infrastructure

    MariaDB solution engineers will share best practices for DBAs in the areas of HA/DR, performance, scalability and security as well as recommendations and tips for migrating from Oracle Database and how to get started with containers using Docker Compose, Kubernetes Helm charts and Red Hat OpenShift.

    Click ‘See More’ to view sessions in this track

    See More

    Deploying MariaDB for HA on Google Cloud Platform

    Google Cloud Platform (GCP) is a rising star in the world of cloud infrastructure. Of course there is Google CloudSQL, but sometimes you need more control over your databases. In this session, Matthias Crauwels of Pythian will guide attendees through the process of deploying and managing MariaDB in the cloud on GCP.
    _______________

    Creating a complete disaster recovery strategy

    In this session, we will discuss all of the disaster recovery features and tools available in MariaDB, including MariaDB Flashback for point-in-time rollback, MariaDB Backup for incremental backup/restore, delayed replication and dedicated/tiered databases for backups.
    _______________

    Getting started with Docker sandboxes for MariaDB

    MariaDB recently introduced a pair of Docker sandboxes for running MariaDB clusters. The sandboxes, using Docker Compose, make it easy to run a local MariaDB cluster for transactional and/or analytical processing. The transactional sandbox starts up a MariaDB cluster with replication and automatic failover while the analytical sandbox starts up a MariaDB AX cluster with sample data and an Apache Zeppelin notebook.
    _______________

    How to migrate from Oracle Database with ease

    MariaDB introduced Oracle Database compatibility last May with support for Oracle Database data types, sequences, stored procedures (PL/SQL) and more, making it easier than ever to migrate to MariaDB. In this session, we will share best practices and lessons learned from our experiences helping customers migrate from Oracle Database. In addition, we’ll explain how we approach migrations, what’s needed to complete a successful migration and the tools we use to determine the level of effort required.
    _______________

    Using all of the high availability options in MariaDB

    MariaDB provides a number of high availability options, including replication with automatic failover and multi-master clustering. In this session, we’ll provide a comprehensive overview of the high availability features in MariaDB, highlight their impact on consistency and performance, discuss advanced failover strategies and introduce new features such as casual reads and transparent connection failover.
    _______________

    Optimizing MariaDB for maximum performance

    When it comes to optimizing the performance of a database, DBAs have to look at everything from the OS to the network. In this session, we’ll share best practices for getting the most out of MariaDB. We’ll highlight recommended OS settings, important configuration and tuning parameters, options for improving replication and clustering performance and features such as query result caching.
    _______________

    Getting the most out of MariaDB MaxScale

    MariaDB MaxScale is the world’s most advanced database proxy, and while the most common use case is for it load balancing and automatic failover, it can do much more. In this session, we’ll explore the variety of things you can do with MariaDB MaxScale. We will look at the database firewall, the LUA script module, the hints filter and other ways to take advantage of MariaDB MaxScale.
    _______________

    Running MariaDB in multiple data centers

    MariaDB is often deployed in multiple data centers for high availability and/or disaster recovery. In this session, we’ll walk through real-world use cases and the topologies customers have created to leverage multiple data centers. In addition, we’ll discuss important considerations and how to address them, as well as more advanced options such as dedicated binlog servers for cross–data center replication.
    _______________

    Configuring workload-based storage and topologies

    MariaDB has multiple workload-optimized storage engines, including InnoDB for mixed workloads, MyRocks for write-intensive workloads, Spider for scalable workloads and ColumnStore for analytical workloads. In this session, we’ll discuss how to choose the right storage engine for individual tables, and how replication and asymmetric topologies can be used to further optimize MariaDB and the hardware it runs on for specific workloads.
    _______________

    Deploying MariaDB for extreme scale

    MariaDB can scale reads, writes and storage using sharding and replication. In this session, we’ll examine different scalability strategies for MariaDB, from scaling up in anticipation of peak workloads to scaling out with transparent, built-in sharding or read replicas with a dedicated replication server (i.e., binlog server), separating analytical queries, and running them on dedicated storage.
    _______________

    Using advanced security and data-protection features

    MariaDB has the most comprehensive set of security of features available in an enterprise open source database, rivaling those of proprietary databases. In this session, we’ll explore some advanced security capabilities, including the built-in database firewall and data masking, both needed to fully protect personally identifiable and/or sensitive personal information (PII/SPI). In addition, we’ll take a look at the new security features in MariaDB Server 10.4, from client-side encryption to password-crack detection.
    _______________

  • Modern application development

    Learn how to build web, mobile and Internet of Things (IoT) applications and microservices in Java, .NET and Node.js using modern SQL, built-in JSON functions, geospatial objects, temporal queries and user-defined functions – and how to write powerful but elegant queries with ease.

    Click ‘See More’ to view sessions in this track

    See More

    The role of databases in modern application development

    The rise of serverless, microservices, event-driven application architecture, or full-stack development with JavaScript and the MEAN stack, is changing what application developers need from databases – and how they interact with them. In this session, we’ll discuss recent advancements in application development and architecture and explain how MariaDB supports them.
    _______________

    How to leave the ORM at home and write SQL

    Looking to understand the basics of relational databases and the ubiquitous structured query language (SQL)? This is the session for you. We will start with an introduction to relational database theory and quickly move to practical examples of SQL with simple, single-table selects, joins, and aggregates. If you’re ready to get your feet wet, whether you’re a Java ace or a front-end wizard, come learn from the experts on all things SQL.
    _______________

    Query hierarchical data the easy way, with CTEs

    With common table expressions (CTEs), it’s easy to write recursive queries and query hierarchical data such as graphs – a lot easier than using a specialized graph database or writing complex client-side code. In this session, you’ll learn about the surprising number of places where graph data appears in modern applications and how to efficiently store and query it using MariaDB and common table expressions.
    _______________

    Getting started in the cloud for developers

    Looking to get up and running in the cloud, and start building applications with MariaDB as fast as possible? This session will walk through the quick-start process of deploying MariaDB in the most popular public clouds. In addition, we will touch on some of the essential differences between cloud database services, helping you to create the cloud database strategy that best meets your needs.
    _______________

    Discovering and querying temporal data

    Did you know MariaDB Server is the only open source database to implement temporal tables per the SQL specification, allowing you to query data as it existed at a previous point in time? MariaDB Server 10.3 uses system-versioned tables and MariaDB Server 10.4 uses system- or application-versioned tables. Whether it is for reporting and analysis or fine-grained data recovery, temporal data and queries can change the way you think about and manage data. In this session, you’ll learn how this game-changing feature can be used to tackle problems that were simply not solvable before.
    _______________

    Writing powerful stored procedures in PL/SQL

    Oracle Database compatibility in MariaDB Server lets developers choose between ANSI SQL and PL/SQL when writing stored procedures. MariaDB Server 10.4 is extending Oracle Database compatibility further by adding CONNECT BY and additional syntax. In this session, we’ll focus on how to write powerful stored procedures and functions with PL/SQL, whether you’re migrating from Oracle Database or not.
    _______________

    Building better Node.js on MariaDB

    Come learn tips and tricks for using the new Node.js connector for MariaDB. Recent driver updates include exciting new features such as a promise-based API, pipelining and insert streaming. Targeted at beginner to intermediate Node.js developers, this session will include basics for getting started with Node.js before focusing on best practices and more advanced topics. We’ll finish with an overview of integration with well-known Node.js frameworks, including the popular objection/relational mapping (ORM) frameworks.
    _______________

    Using advanced options in MariaDB Connector/J

    MariaDB Connector/J is our widely used Type 4 JDBC driver for Java. This session will cover the basics of getting started with Java and MariaDB, and will move quickly to more advanced topics, including connection pooling, automatic failover and debugging. We will also include an overview of popular object/relational mapping (ORM) and programming frameworks for Java. Even if you have been using the MariaDB Connector/J for years, come to this session to learn about the latest release, see where the connector is going and discover the latest tips and tricks.
    _______________

    Moving to hybrid relational/JSON data models

    While some data is best modeled as rows, other is best modeled as JSON documents. JSON is the de facto standard for REST and microservices. MariaDB is the leading enterprise open source relational database, but it includes a comprehensive set of SQL functions for storing, indexing and querying JSON documents, too. In this session, you’ll learn how to extend relational data models with JSON documents to get the flexibility and agility you need when building modern applications.
    _______________

    Extending MariaDB with user-defined functions

    Learn how to write user-defined functions (UDFs) as stored functions or C/C++ extensions. While MariaDB Server provides a wide range of built-in functions defined in the SQL specification, some applications can benefit from custom-built, server-side functions. Want to build a function to calculate the Tanimoto coefficient between two chemical compounds or genes? In this advanced session, we will get you started writing UDFs that could give you a leg up on the competition.  
    _______________

    How to power microservices with MariaDB

    Adoption of microservices is continuing at a rapid pace, but many deployments continue to struggle when it comes to the database topology and data modeling. This session will cover the pros and cons of different approaches (e.g., giving every microservice its own database or its own schema on a shared database) and various strategies for providing a consolidated view of data when different data is managed by different microservices.
    _______________

    Getting started with the new Python connector

    The last several years have seen a surge of interest in Python. In fact, it has become the go-to language for data scientists working on AI and machine learning. In this session, we will introduce MariaDB Connector/Python, currently in development. We’ll demonstrate how to build Python applications on MariaDB, including those taking advantage of Python’s powerful machine learning libraries.
    _______________

    Evaluating connectors for modern .NET development

    When it comes to .NET development on MariaDB, you have a couple of options. In this session, we’ll take a look at various community and commercial .NET connectors compatible with MariaDB. We’ll discuss the differences between these connectors, what they do and don’t support (e.g., ADO.NET and LINQ), and the pros and cons of different approaches to .NET development on MariaDB.
    _______________

  • Scalable interactive analytics

    Get to know MariaDB AX and discover how innovators are using distributed, columnar databases to query hundreds of billions of rows in seconds with ad hoc, interactive queries (and no indexes) – and how to incorporate streaming data and machine learning with Apache Kafka and Apache Spark.

    Click ‘See More’ to view sessions in this track

    See More

    Understanding the architecture of MariaDB ColumnStore

    MariaDB ColumnStore extends MariaDB Server, a relational database for transaction processing, with distributed columnar storage and parallel query processing for scalable, high-performance analytical processing. This session will help MariaDB users understand how MariaDB ColumnStore works and why it’s needed for more demanding analytical workloads, and will cover:

    – Use cases
    – Query processing
    – Bulk data insertion
    – Distributed partitions
    – Query optimization

    _______________

    What’s new in MariaDB ColumnStore

    In this session, we will walk through new features of the MariaDB ColumnStore storage engine, tools and adapters, and provide a sneak peak at what we’re planning for the next release.
    _______________

    Modeling data for scalable, ad hoc analytics

    There are many ways to model data for analytics (e.g., star schema), but when it comes to MariaDB ColumnStore you no longer have to model and index data for specific queries. However, you have to keep in mind the data is stored by column and distributed. In this session, we’ll share best practices for data modeling with MariaDB ColumnStore, noting what works really well and when, and what doesn’t.
    _______________

    How to make data available for analytics ASAP

    There are many ways to import data into MariaDB ColumnStore, including command-lines tools for importing files. However, a combination of bulk and streaming data adapters makes it easy to import data on demand, without having to wait for a scheduled job. We show all of the ways to import data, from manual imports to more advanced options such as C++, Java and Python data adapters, Apache Spark, change-data-capture streams and Apache Kafka message queues – all of which can be used to import data on demand so it’s available for analytics as fast as possible.
    _______________

    Exploring modern analytics use cases

    Analytical workloads are fast exceeding what traditional databases and data warehouses are capable of, with businesses needing to store a lot more data (and for longer periods) while empowering their customers to analyze it – in real time, and in unexpected ways. In this session, we’ll describe modern analytics requirements and explore how MariaDB ColumnStore is helping customers meet them, via real-world use cases.
    _______________

    Using Pentaho with MariaDB ColumnStore

    In this session we show how the Pentaho connector for MariaDB ColumnStore can be used both for BI/reporting on MariaDB ColumnStore and for loading data into MariaDB ColumnStore.
    _______________

    Applying linear regression and predictive analytics

    In this session we will introduce the linear regression and statistical functions that debuted in MariaDB ColumnStore 1.2, and how you can use them to support powerful analytics. We’ll also explain how to perform even-more-powerful analytics by writing multi-parameter user-defined functions (UDFs) – also new in MariaDB ColumnStore 1.2.
    _______________

    Check back soon for more sessions offered in this track!

Agenda Overview

Morning
Afternoon
Evening
Day 1

February 25

Registration
Workshops
Training

Workshops
Training

Day 2

February 26

Registration
Keynotes
Breakout sessions

Breakout sessions
Lunch

Reception

Day 3

February 27

Registration
Breakout sessions

Breakout sessions
Lunch

Reception

Background Divider Element

What to Expect

Meet

MariaDB’s annual user and developer conference brings together technical experts and practitioners for an information-packed three days at the Conrad Hotel in New York City.

Learn

DBAs, developers, architects and IT executives will get an inside look into the MariaDB product vision and roadmap, plus sneak peeks at projects currently in development.

Collaborate

OpenWorks offers an unparalleled opportunity to learn about open source strategies and best practices in infrastructure modernization directly from MariaDB customers.