Since Gluent’s inception, we’ve described the “New World” of data and how we see the hybrid approach to data management and data access being the future. A centralized modern data storage location with seamless data access via our smart connector from various relational databases, requiring no changes to the applications accessing the data. We typically describe the modern data platform as being Hadoop (and HDFS), but we’ve never really specified exactly where Hadoop was implemented. It could be on-premises or in the cloud, and in some cases we don’t even need HDFS at all. Let’s dive a little deeper into the Gluent Data Platform cloud story.
First off, why cloud? For many enterprises, moving data to the cloud means cost savings. No infrastructure to maintain means the hardware maintenance and upgrades are taken care of for you, with the cost rolled into the overall cloud provider fees. Provisioning of a new environment is much quicker as well. Outsourced managed services and support will take care of any backend issues, as well as perform upgrades, automatic backups, and data archiving. The ability to scale compute and storage resources is a given, ramping capacity up or down as needed for various workloads. With cloud, you pay for what you use, providing a more flexible and less expensive infrastructure and making the business much more agile and adaptive to change.
Even with all of these benefits, many enterprises have not yet adopted the cloud. Some have found it difficult to run their existing databases in the cloud due to large data volumes and performance requirements. Others have found it hard to move all the rest of the application infrastructure that is closely dependent on the central database in one go. Data security and governance rules are also limitations for many. Due to these common obstacles, countless companies have not been able to make the move to cloud data systems. At Gluent, we believe our platform can help alleviate some of these challenges and enable all enterprises to adopt the cloud as a part of their data management and storage architecture. Gluent Data Platform lowers the bar for cloud adoption!
Gluent’s approach to cloud
Migration of relational databases to cloud storage is one of the more common uses of the cloud, allowing enterprises to harness many of the advantages listed above. The Gluent Offload functionality will sync your RDBMS data to cloud storage and keep it in-sync via incremental updates. No data streams or ETL to set up, just a simple command. Let’s face it, Gluent is like pushing the easy button for cloud migrations.
However, moving mission critical databases to the cloud without compromising performance (sometimes severely) can be quite a challenging task. And while shifting to a cloud-native database platform may help with query performance, the applications will require a massive code rewrite. A hybrid approach gives you the best of both worlds – great query performance even over very large datasets, with no need to rewrite your application code. In the new hybrid world, databases in the cloud can operate as fast as on-premises database appliances, continuing to meet the performance requirements of the business.
Other use cases for moving data to the cloud take advantage of the cloud infrastructure and its inexpensive and expandable storage. Backups, data archives, and disaster recovery are typical scenarios which require an endless amount of storage space for the ever growing volume of enterprise data produced every day. And yes, the data must remain accessible as well, either from cloud based query services or in a disaster recovery switchover/failover scenario. There is also a big push around the use of serverless technologies in the cloud. Interactive query services, analysis tools, and data integration processes that do not have any hosting fees associated (they just charge for amount of data processed or queried), can spin up as much computation power as needed behind the scenes to get the job done.
Gluent Data Platform is capable of migrating RDBMS data to Hadoop in the cloud, and has been for some time now. But not all of your enterprise data begins as tables in a relational database. Some start out in Hadoop tables with the data stored as files in the underlying, on-premises HDFS environment.
When migrating your organization’s data to the cloud, you cannot ignore Hadoop native tables simply because the data is not stored in a relational database.
Introducing Gluent Cloud Sync, the latest product release from the Gluent team. Cloud Sync is used to synchronize native Hadoop tables to the cloud. That’s right, tables! The process will sync the underlying data from tables to cloud storage, such as HDFS, AWS S3, Google Cloud Storage, etc, and will also copy the table metadata from the source to target, ensuring the table remains accessible and looks just as it did in the original environment. The Cloud Sync process can be orchestrated to ensure the latest data is always available in the remote location. Gluent can sync your new world data to the cloud!
Cloud Sync has three primary functions: backup, restore, and clone. The Backup process is what we use to copy Hadoop tables to a cloud or on-premises environment, as just described. This copy can be for pure backup purposes, archiving stale data, or even as a disaster recovery option. If something goes awry with your primary data source, the Cloud Sync Restore functionality can recover any lost data from the backup system. The Clone capability of Cloud Sync is built to create an exact copy of the source HDFS data and Hadoop tables in another local or remote location. This makes it easy to migrate from your on-premises datacenter to the cloud or to another datacenter.
Over the course of the next few weeks, we’ll describe several of the Gluent cloud use cases in further detail, including some of the following:
- Data Migration – Gluent is the easiest way to move data from relational databases to the cloud. So simple, it’s like an easy button for cloud database migrations!
- Cloud Hybrid World – Use the distributed computation power of Hadoop to help your Oracle database fly in the cloud. The hybrid approach is your solution to Oracle database performance challenges faced by cloud vendors.
- Cloud Sync for Backup or Disaster Recovery – Store data in AWS S3 or Microsoft Azure as a backup or HDFS in the cloud for Disaster Recovery. Better yet, the backup data can be used for further analysis or integration with serverless, cloud based technologies.
- HDFS Cloning – Spin up a cloned environment for your data science / machine learning work in a separate environment.
Keep an eye on the Gluent twitter feed (@gluent) or subscribe to our newsletter to ensure you have the latest blog posts from our team. If you can’t wait and want to learn more about Gluent’s cloud offerings, including the recently released Gluent Cloud Sync, drop us a line at email@example.com.