Companies use several special-purpose databases as they can’t find a single database that meets the application requirements. However, this leads to complexity in moving data between the systems. Rick Negrin, VP of product management, SingleStore, talks about database sprawl and how companies can avoid it.
Data infrastructure complexity is running rampant within today’s enterprises. And for many businesses, there is no end in sight to this messy and, ultimately, dangerous state of affairs.Â
Complexity arises as organizations onboard special-purpose databases to enable new applications or expand on existing ones. Adding a special-purpose database for every need may scratch an immediate itch. But it leads companies to amass large collections of databases.Â
Some companies now have dozens of specialty databases they need to support. Database sprawl adds cost, wastes resources, and can impede the ability to power valuable new applications.Â
That, in turn, makes companies slower, less agile and unable to compete effectively in the marketplace because they cannot deliver the experiences their customers want and need.
Database Sprawl Creeps up on Companies, and Then — Bam! — It Hits Them Where It Hurts
You may be asking yourself: How can this happen? More importantly, you may wonder: How can I correct the course to ensure my company does not get crushed by database sprawl?
The reality is that most companies are not even aware that they are on a collision course with database sprawl. It is a case of business as usual. As companies move to address each new application, they simply add a new database for every need. Or they find that an existing application needs additional data sets, greater scale, or more capabilities. So, they simply add a specialty database to the mix. But the result of this approach is anything but simple.Â
This results in several database systems and the resulting data movement between them. This is hard to design, implement, manage and troubleshoot. The added complexity slows down performance and makes the platform less stable.
Don’t Fall Into the Trap of Believing That Special-purpose Databases Are Always the Answer
Modern, data-intensive applications must be available around the clock and updated in real-time, with the most current data, to deliver the kinds of experiences that users expect.
The demands of modern applications have led many companies to mistakenly believe they need more special-purpose databases. This is a result of the legacy general-purpose databases not being up to the task of supporting the modern application requirements. That is largely why the number of special-purpose databases has ballooned in recent years. With the proliferation of open source and the cloud, you might have hundreds of special-purpose database options from which to choose.Â
But, in most cases, you do not need to waste your time and energy navigating through all of these choices, implementing yet another special-purpose database and then contending with database sprawl. Only a tiny fraction of total workloads truly need specialty databases.Â
That is welcome news as ensuring the performance that today’s data-intensive applications need is just not possible when you must move data between a large collection of data silos and your existing data infrastructure limits your availability, performance and scale.Â
See More: 4 Practical Ways to Tackle SaaS Sprawl Effectively
Take a Broad View in Assessing What Your Applications Need Both Now and in the Future
The first step in getting a handle on what data infrastructure you really need is to consider all aspects of how you use data today and how you expect to use data going forward.Â
This may seem obvious, yet many organizations do their testing and capacity planning in isolation on a small data set and only consider one or two dimensions. But, in production environments, data is often ingested all the time, multiple users do different things simultaneously, and you may have maintenance operations running as well. Now that the system is facing real-world demands, what worked for a single query running in isolation does not work anymore.
Avoid the element of surprise. Take a broad view of your data, requirements and future. Assess your data size, ingestion rate and query complexity, and concurrency and latency requirements. Consider what kind of growth you expect in each of these dimensions.
That will put you in a much better position to determine which data infrastructure best meets your needs. You can select a database that addresses your workload and will scale as usage grows. You can avoid database sprawl and deploy and manage only the data infrastructure you truly need to support your applications, including your data-intensive applications.
Simplify Your Data Infrastructure With a Single, Multi-model, Ultra-fast Database
As you work to address the needs of data-intensive applications and avoid data infrastructure complexity, be aware that in the vast majority of cases, a single modern, scalable, relational database can support all of your application requirements across the cloud and on-premises.
When you set out to find such a database, select one that supports transactions and analytics in a single database. This will help you to simplify your data architecture and avoid data sprawl.Â
Make sure your single database is up to the task of delivering the ultra-fast speed and elastic scalability you need to create and deliver breakthrough experiences. Choose a database that is built for the cloud, supports complex analytical queries, and delivers fast query responses for real-time and historical data. Ensure that the modern database ingests data continuously while performing concurrent analytics at scale. Adopt a database that supports multiple data models, including JSON, relational, time-series, geo-spacial and full-text search.
See More: How to Tame Cloud Identity Sprawl
Consider the Business Results That Other Leading Companies Have Been Able To Achieve
Research what other companies have achieved by moving away from complex data infrastructure and adopting a single modern database to address data-intensive applications.
A popular online gaming network wanted to ingest 1 million rows per second and support ANSI SQL analytics. It could not address this data intensity challenge and get all the other features it needed with its collection of technology, which included DynamoDB, ElastiCache, and Postgres. But after adopting a single real-time distributed SQL database designed for data-intensive applications, it was able to ingest 1 million events per second, execute complex SQL queries, and enjoy a 100x improvement in performance and a 4x reduction in the total cost of ownership (TCO).
One of the world’s leading streaming entertainment providers was using Druid and Storm for data aggregation and analytics to understand customer experience and predict regional issues. The system went out during the Super Bowl, prompting the company to find a better solution. With its single, modern database, the company gained total visibility, stability and lower TCO.
In the past, one of the world’s largest banks relied on ten open-source technologies. This prevented it from getting anywhere close to the 50-millisecond response time it needed to execute more than 70 concurrent queries for its real-time payment card transaction fraud detection application. But the company got the performance it needed while simplifying its data infrastructure and eliminating database sprawl by replacing those ten systems with just one open-source solution paired with its new single, multi-model database.
Adopting a single, high-performance database may well be the answer to your data-intensive challenges, too. It can also help you to avoid the painful problem of database sprawl. And it can empower you to use your resources better and deliver differentiated customer experiences.
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