Introduction
If you're like most data scientist, analysts, or developers, you probably spend a lot of time worrying about your ever-growing store of data. After all, it's the lifeblood of your business. You need to ensure that it's properly stored and accessible when you need it. This article will discuss the benefits of using elastic databases and common migration mistakes to avoid. We'll also provide some tips on optimizing your database for performance.
A recent survey from IDC, found that one-third of enterprises have already migrated or migrated their applications and data centers to public cloud infrastructures such as Amazon Web Services (AWS) or Microsoft Azure. This is an ongoing trend for companies looking to optimize costs while also preparing for future demands on capacity and efficiency.
However, these migrations don't come without their challenges - ensuring that data integrity is maintained during the transfer between environments.
Elastic Databases To Mitigate Data Risks
One method to mitigate these risks is by using elastic database technologies that support the portability and movement of data sets between SQL Server, Oracle, MySQL, or other data stores. This is where elastic databases come into play. An elastic database is a distributed system that makes it easy to store and access large amounts of data by spreading it across many servers, also known as nodes. It provides transparent scalability with no downtime or interruptions. As a result, you can easily use elastic databases to build web applications in the cloud.
Elastic databases are designed for fast retrieval of data using caching, sharding, and partitioning techniques where data is divided into chunks called elastic units. These elastic units are written to separate partitions on different machines to be read independently. Each elastic unit has metadata that contains the type of unit, its owner (which machine it was assigned), and time of creation.
Using elastic units, elastic databases can scale to process more data at once by creating additional partitions and assigning units to them. The concept behind an elastic database is to take the idea of virtualization, which has led to significant efficiencies for server storage and use in data centers and apply it to databases.
By applying this concept, elastic databases can support multiple concurrent users or workloads while delivering strong performance levels. In addition, with this capability, organizations can migrate their entire databases or subsets of data into the cloud, manage it all within a single cluster, and then move that information back to an on-premise infrastructure.
The application of elastic databases has become increasingly popular because they make migration projects simpler, faster and less expensive than previously possible. This is good news for data professionals looking to take advantage of advances in cloud-based infrastructures while maintaining good performance.
The Benefits Of Elastic Databases
Here are some of the key benefits that elastic database technologies offer during migration projects:
Access to Cloud Environments: By moving data sets into the cloud, businesses can achieve faster time-to-market, higher competitive advantage on new products and services, and lower costs through more efficient resource utilization.
Increased Data Portability: Elastic databases can transfer data between cloud-based environments with little to no performance degradation during the process. As a result, organizations can test their applications in the cloud without the risk of disrupting production accounts.
Increased Database Elasticity: The ability to scale out across multiple cloud environments allows for improved performance, higher levels of data availability, and faster time-to-market. Elastic databases also provide load balancing capabilities that enable companies to distribute workloads across systems without building complex infrastructures automatically.
Reduced Risk of Data Loss: When migrating data, organizations can lose information. However, by moving primary databases into the cloud, this risk is significantly reduced because businesses can have their entire database in one place with its information replicated to other locations. Therefore, if anything happened with one database, all others would remain available.
Greater Database Availability: By placing multiple databases within a single cluster, organizations can achieve higher uptime because more systems are available to ensure workloads are always handled regardless of demand. This also means that there is no need to worry about double provisioning or creating environments for testing purposes. As a result, companies can significantly reduce their operating costs because they will spend less time managing databases and more time working with customers.
Better Organizational Agility: Elastic allows organizations to adjust their resource levels without downtime, enabling businesses to achieve faster time-to-market and increase overall productivity by using existing resources better. In addition, they can easily create new development environments for testing purposes which is a big advantage in building and releasing new products and services.
Common Mistakes When Migrating
Migrating your data after elastic has started
Migration to an elastic database should always be done when it's near or at idle. Once you start migrating, you will see where your current limits are for what elastic can ingest so you can plan for the peaks. It is beneficial to have an elastic start-up in production on a low CPU to see how elastic will perform during peak hours.
Excessive vertical scaling
Sometimes you can have too much elasticity in your application architecture. For example, this can happen when you design a system with only one computing unit because you do not want any downtime. Now you have only one server to scale vertically until it reaches maximum capacity.
This approach gives limited availability and no redundancy in hardware failures unless you implement replication or failover systems yourself.
Elastic databases are designed to scale horizontally and perform better that way. So follow the elastic approach and implement a multi-node elastic architecture for your applications.
Replicating instead of failover
In case of failure on one node, replication is often implemented instead of failover for simplicity. However, this approach slows down your application because it has to reset and reload upon recovery, especially if multiple nodes are in production.
Use elastic databases with failover scripts. Your architecture will be highly available and scalable, so you can just add another node in case of hardware failures or traffic peaks.
Not using backup/recovery
Elastic databases offer a reliable way of backing up data with point-in-time recovery. At the same time, elasticity makes storage space nearly infinite on-demand by adding more nodes whenever migrating to elastic databases.
These days, the most commonly-used backup method for elastic databases is simply copying units from one node to another. Backups work very quickly since each unit contains metadata about its size and location on disk, so only changed portions will get copied during a restore. This makes restoring elastic databases reasonably easy if you have recent backups of all your nodes.
Backup/recovery is included in elastic databases, so you don't have to do it manually or with external tools.
The best way to deal with data loss is to prevent it from happening in the first place. Implement backups at different points in time into your application stack, configure elasticity properly, and elastic databases will take care of the rest.
Incorrect server deployments
During elastic database migrations, it is highly recommended to use indexing and create mapping documents for elastic so that no data is lost during migration. During the migration process, elastic should be hosted on separate servers, and elastic should not use the same host as the elasticsearch node. Elastic should always have dedicated volumes and dedicated network interfaces.
Moving all your data at once
One common mistake when moving to elastic databases is moving all data from the start. While this might seem like a good idea, it often leads to the server database lacking the required capacity and performance when new applications need to use elastic databases.
Once the business value has been identified for elastic databases, you need only migrate the necessary data while also ensuring that it does not impact running applications before or during any migration process.
Not using a migration tool
While elastic databases are similar to relational database management systems, many differences exist. This means that converting existing relational technology into elastic technologies can be extremely difficult, if not impossible, given the level of complexity in some organizations.
Therefore, you must convert your data using elastic database tools that are elastic database ready. ShardingSphere's ElasticJob is an excellent example of an open-source tool that helps you migrate your data to a flexible database. ElasticJob is a distributed scheduling solution consisting of two separate projects, ElasticJob-Lite and ElasticJob-Cloud.
ElasticJob-Lite is a lightweight, decentralized solution that provides distributed task sharding services; ElasticJob-Cloud uses Mesos to manage and isolate resources. In addition, it uses a unified job API for each project. As a result, developers only need code one time and can deploy at will.
Conclusion
As more data is generated every day, organizations need to rethink managing their data infrastructure. This is especially true for Database Management Systems (DBMS), which can be complex and time-consuming to maintain.
As a result, companies must consider solutions that offer more flexibility and additional benefits such as lower operating costs and higher levels of availability. Cloud-based providers are offering these types of database technologies. They have been referred to as elastic databases because they can expand with changing business needs that traditional database solutions cannot.
This allows companies to respond more quickly to market demands without sacrificing the levels of service that their customers expect. In addition, organizations can save money when it comes to purchasing server hardware and software licenses because elastic databases are offered as pay-as-you-go services which are very attractive to businesses of all sizes.
This allows companies to use existing budgetary allocations more efficiently and free up time and funds to focus on other areas that can help them grow their business.