Why Consider a Hadoop to Databricks Lakehouse Migration?
Hadoop offers the option to maintain huge on-prem workloads but enterprises need to migrate this data into cloud-based managed services...
As billions of internet users exchange information with each other and as platforms diversify, data grows exponentially together with the complexity to manage, organize, and analyze it. Companies are faced with dull data architectures that require better solutions, and the ideal alternative that exists is called change streaming.
Change streaming relates to the direct display of data changes in real-time from a source (usually a database) to the destination.
Change streaming relies on change data capture (CDC) patterns to replicate and move data so that major disruptions from having too many hands in the data flow can be mitigated. Google Cloud recently released Datastream, their novel replication and data capture service completely serverless and available to anyone interested.
Datastream joins the data science stage with its much-needed features to streamline database replication, provide real-time analytics, and support event-driven architectures. It unifies the data found in separate storage systems, databases, and applications with maximum speed and minimum latency.
Let’s explore how Datastream allows you to deliver change streams from MySQL and Oracle into Cloud Spanner, BigQuery, and other Google Cloud services.
Datastream allows users to synchronize data across their business faster. Applications and heterogeneous databases will keep working efficiently and without disruptions even after the implementation of Datastream to gather data. Your source will remain intact so that you can work with data and accelerate database replication, support event-driven architectures, process rapid cloud migrations, and build analytics by using data streams.
Users shouldn’t be concerned that high volumes of data would cause latency. Datastream is serverless and it can adapt with ease according to the volume of data presented. It means that you have to spend less time dealing with the infrastructure, maintaining optimal performance, or provisioning resources and dedicate more time to studying the insights derived.
Datastream promises to enhance your experience in working with data on-premises and on the cloud. Here are some of the perks that accompany the implementation of Datastream in your organization:
Datastream finds use in multiple industries where data insights are required. One of their earliest customers is Schnuck Markets, Inc, the giant supermarket retailer with over 100 stores. They used Datastream to replicate and monitor data into BigQuery which proved more effective than using on-premises.
Would Datastream be useful for your business? It depends on whether its capabilities are a match for your current infrastructure. Here are some of its potential implementations:
Getting started with Datastream can be done in a straightforward process of six steps. Then, you’re all ready and set to stream real-time changes from MySQL and Oracle databases through Datastream.
Now, you’re all set to start data streaming!
Datastream is appropriate for various applications because it offers both cloud and on-premises support. It makes it possible to capture changes and historical data into Cloud Storage from all MySQL sources and Oracle. Moreover, it integrates with Dataflow and Cloud Data Fusion to deliver replications to multiple Google Cloud destinations.
We believe using data analytics is crucial for every organization, and we have found this by working on over 100 projects with organizations of different sizes. Making use of machine learning, data science, and multiple other tools, we help unify data in one place to portray useful insights that can be used for more accurate business decisions. Read more here.