A distributed relational database can do wonders for the scalability of your application. Unfortunately, there are a number of challenges that tend to accompany this modern solution.
The short presentation identifies the issues that many of us working with distributed databases know all too well.
Looking at each challenge individually, you will learn how to identify these common nuisances in a distributed database environment.
The first post in this series, Query Execution Paths in a Distributed Relational Database Environment: Part 1, I briefly discussed the different ways one could go about executing an SQL statement.
Sticking with the concepts described in that post, I would now like to delve a bit deeper into the various execution paths, using specific examples to understand and analyze the collection and processing phases of queries.
Today, I’d like to discuss read/write (r/w) splitting – use cases and benefits.
Read/write splitting is a special kind of data distribution, and it offers a slightly different approach to a number of database scalability issues. Essentially, the r/w splitting process takes place in a simple cluster where multiple copies of the entire database are utilized for query execution (instead of distributing portions – or shards – of data).
So, let’s take a look at some typical uses cases and some specific issues you need to take into account.
Your business is taking off and success feels good! Users are flocking to your app. Your game is going viral. Website traffic is exploding. Your hard work is paying off. Congratulations!!
Business growth creates more users, more transactions, and more data and can strain your database beyond its capacity. But your database must keep up with the rise in transactions and concurrent workloads. What can you do? A short-sighted solution is to buy bigger hardware and scale up. But this only provides a temporary fix. A long-term solution is to scale out your database. That is, transition from a single instance database to a distributed database.
But how can you scale out an existing database without downtime and without any application or service interruptions?
That’s what I want to discuss today.
We’re proud to announce today that ScaleBase’s distributed relational database management system, built on MySQL and optimized for the cloud, is now available on IBM Cloud Marketplace.
IBM customers can use ScaleBase’s BlueMix enabled software to create a distributed MySQL database with unlimited scalability and transaction throughput.
Distributed relational databases and cloud-based distributed computing resources are a perfect match for applications moving to, or already in, the cloud.
This presentation quickly looks at a common and particularly difficult situation: what we call the ‘shard conflict’.
In addition to defining what a ‘shard conflict’ actually is, you will learn how to identify and resolve these conflicts within a distributed relational database, as well as understand how they affect query processing.
Data Distribution Policy, Part 3: Change Scenarios Your Distributed Relational Database Must Accommodate
In Part 1 of this article series about creating a distributed relational database, we saw that distributed databases are a perfect match for Cloud computing models and distributed Cloud infrastructure. In Part 2, we discussed finding the best data distribution policy for database scalability and performance specifically tailored to your unique application, based upon a guided analysis of the nature of your data, data relationships and the functional use of your data.
Today, in Part 3, I want to discuss distributed database efficiency over the long haul, as application usage patterns, user requirements and workloads change.
Database Distribution Policy, Part 2: How to Analyze and Create the Best Distribution Policy for Your Application
In Part 1 of this article series about creating a distributed relational database, we saw that distributed databases are a perfect match for Cloud computing models and distributed Cloud infrastructure. As such, they are the way forward for all new applications and bring web scale capabilities to existing applications.
Distributing data across a cluster of smaller database instances and maintaining full relational database integrity, two-phase commit and rollback, as well as leveraging SQL, is today’s state of the art for distributed relational databases.
The natural question we are lead to ask is: “OK, So what is the best way to distribute data for my applications and my workloads?”
That’s what I want to discuss today.
We’re proud to announce today that ScaleBase’s Distributed Relational Database Management System, built on MySQL and optimized for the cloud, is now available for Amazon Web Services (AWS) in AWS Marketplace.
“We welcome ScaleBase to AWS Marketplace with their Distributed Database,” said Terry Hanold, Vice President, Cloud Commerce, Amazon Web Services, Inc. “Customers with growing application and MySQL database requirements can benefit from migrating to a scalable, virtualized deployment on the cloud.”
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