Reliable access to data is vital for companies to thrive in this digital age. But businesses struggle with various risk factors- like hardware failures, cyberattacks, and geographical distances-that could block access to data or corrupt valuable data assets. Left without access to data, teams may struggle to carry out day-to-day tasks and deliver on important projects.
One way to safeguard your data from those risks is using datareplication solutions. This technology is indispensable for teams that want to replicate and protect their mission-critical data and use it as a source of competitive advantage.
To help businesses explore datareplication, we’ll dive into this technology and cover its benefits, challenges, types, and methods. Lastly, we’ll explore what features you should look for in datareplication software.
Data replication is the process of copying data from an on-premise or cloud server and storing it on another server or site. The result is a multitude of exact data copies residing in multiple locations.
These data replicas support teams in their disaster recovery and business continuity efforts. If data is compromised at one site (for example by a system failure or a cyberattack), teams can pull replicated data from other servers and resume their work.
Replication also allows users to access data stored on servers close to their offices, reducing network latency. For instance, users in Asia may experience a delay when accessing data stored in North America-based servers. But the latency will decrease if a replica of this data is kept on a node that’s closer to Asia.
Data replication also plays an important role in analytics and business intelligence efforts, in which data is replicated from operational databases to data warehouses.
How data replication works
Data replication involves copying data in many different ways, including between on-premises servers, servers in other locations, to multiple storage devices, or to or from cloud servers.
Data can also be replicated on demand or according to a schedule, in real time or in batches. Replication can also be triggered by any changes in the master source.
Data replication steps
Overall, the process of data replication follows these steps:
Specify your data source and destination
Choose tables and columns to be copied from the source
Plan out the frequency of replication
Decide on a replication method you’ll use
Identify replication keys if you’re using key-based replication
Select a data replication tool or write a custom code
Monitor replication processes for quality and consistency
Benefits of data replication
Data replication makes data available on multiple sites, and in doing so, provides various benefits.
First of all, it enables better data availability. If a system at one site goes down because of hardware issues or other problems, users can access data stored at other nodes. Furthermore, data replication allows for improved data backup. Since data is replicated to multiple sites, IT teams can easily restore deleted or corrupted data.
Data replication also allows faster access to data. Since data is stored in various locations, users can retrieve data from the closest servers and benefit from reduced latency. Also, there’s a much lower chance that any one server will become overwhelmed with user queries, since data can be retrieved from multiple servers. Data replication also supports improved analytics, by allowing data to be continuously replicated from a production database to a data warehouse used by business intelligence teams.
Replicating data to the cloud
Replicating data to the cloud offers additional benefits. Data is kept safely off-site and won’t be damaged if a major disaster, such as a flood or fire, damages on-site infrastructure. Cloud replication is also cheaper than deploying on-site data centers. Users won’t have to pay for hardware or maintenance.
Replicating data to the cloud is a safer option for smaller businesses that may not be able to afford full-time cybersecurity staff. Cloud providers are constantly improving their network and physical security. Furthermore, cloud sites provide users with on-demand scalability and flexibility. Data can be replicated to servers in different geographical locations, including in the nearby region.
Data replication challenges
Data replication technologies offer many benefits, but IT teams should also keep in mind several challenges.
First of all, keeping replicated data at multiple locations leads to rising storage and processing costs. In addition, setting up and maintaining a data replication system often requires assigning a dedicated internal team.
Replicating data across multiple copies requires deploying new processes and adding more traffic to the network. Finally, managing multiple updates in a distributed environment may cause data to be out of sync on occasion. Database administrators need to ensure consistency in replication processes.
Transactional replication: Users receive a full copy of their data sets, and updates are continuously replicated as data in the source changes.
Snapshot replication: A snapshot of the database is sent to replicated sites at a specific moment.
Merge replication: Data from multiple databases is replicated into a single database.
In tactical terms, there are several methods for replicating data, including:
Full-table replication: Every piece of new, updated, and existing data is copied from the source to the destination site. This method copies all data every time and requires a lot of processing power, which puts networks under heavy stress.
Key-based incremental replication: Only data changed since the previous update will be replicated. This approach uses less processing power but can’t replicate hard-deleted data.
Log-based incremental replication: Data is replicated based on information in database log files. This is an efficient method but works only with database sources that support log-based replication (such as SQL Server, Oracle, and PostgreSQL).
What to look for in data replication software
Data replication software: key features
Data replication software should ideally contain the following features:
A large number of connectors: A replication tool should allow you to replicate data from various sources and SaaS tools to data warehouses and other targets.
Log-based capture: An ideal replication software product should capture streams of data using log-based change data capture.
Data transformation: Data replication solutions should also allow users to clean, enrich, and transform replicated data.
Built-in monitoring: Dashboards and monitoring enable you to see the state of your data flows in real-time and easily identify any bottlenecks. For mission-critical systems with data delivery Service Level Agreements (SLAs), it’s also important to have visibility into end-to-end lag.
Custom alerts: Data replication software should offer alerts that can be configured for a variety of metrics, keeping you up to date on the status and performance of your data flows.
Ease of use: A drag-and-drop interface is an ideal solution for users to quickly set up replication processes.
Data replication software vs. writing code internally
Of course, users can set up the replication process by writing code internally. But managing yet another in-house app is a major commitment of energy, staff, and money. The app also may require the team to handle error logging, refactoring code, alerting, etc. It comes as no surprise that many teams are opting for third-party data replication software.
Use Striim to replicate data in real time
There are also real-time database replication solutions such as Striim. Striim is a unified streaming and real-time data integration platform that connects over 150 sources and targets. Striim provides real-time data replication by extracting data from databases usinglog-based change data capture and replicating it to targets in real time.
Striim‘s data integration and replication capabilities support various use cases. This platform can, for instance, enable financial organizations to near instantaneously replicate transactions and new balances data to customer accounts. Inspyrus, a San Francisco-based fintech startup, uses Striim to replicate invoicing data from its private cloud operational databases to other cloud targets such as Snowflake for real-time analytics.
Striim can also be used to replicate obfuscated sensitive data to Google Cloud while original data is safely kept in an on-premises environment. Furthermore, Striim supports mission-critical use cases with data delivery and latency SLAs. Striim customer Macy’s uses Striim to streamline retail operations and provide a unified customer experience. Even at Black Friday traffic levels, Striim is able to deliver data from Macy’s on-premises data center to Google Cloud with less than 200ms latency.
Have more time to analyze data
Reliable access to data is of vital importance for today’s companies. But that access can often be blocked or limited, which is why data replication solutions are increasingly important. They enable teams to replicate and protect valuable data assets, and support disaster recovery efforts. And with data secured, teams can have more time and energy to analyze data and find insights that will provide a competitive edge.
Ready to see how Striim can help you simplify data integration and replication? Request a demo with one of our data replication experts, or try Striim for free.