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The more moving parts you have, the more likely things are to go wrong.
This is true whether you’re referring to a machine or to a data management strategy.
Today, people like you typically have separate operational databases and analytics databases. So, you’re aware of the challenges of managing and moving data between multiple databases.
To move data from one database to the other, you generally have to run complex ETL (extract, transform and load) pipelines. The most difficult part of data engineering is munging the data together so you can analyze it. You can use ETL to do parts of that in the destination database. That’s simpler because you can use SQL for the transformation part.
But what’s even better is if you don’t have to extract or load your data at all â€“ you can just transform the data in place. This is now possible with SingleStore. With SingleStore, you have the operational schema, and you can transform that into the schema that you use for analytics.
Here’s how one company has reduced complexity and is driving results using SingleStore.
The company, which operates a website that provides vehicle history reports on used vehicles in North America, had been using MongoDB as a document store. But it also needed to build reports. When the company tried to do that using its current database, it took almost 24 hours to process a new day’s worth of data.
Since the company migrated to SingleStore, its operational workloads have gotten faster. But the even more dramatic difference in this company’s experience with SingleStore is how it builds its reports. What used to take hours the company can now do in a few minutes. In addition, the company has fewer moving parts, lowering its data management overhead.
This is a typical scenario that SingleStore, which was previously known as MemSQL, encounters.
Many organizations at first use a specialized database for a narrow set of workloads. As the application evolves, that database may no longer be the best choice. The challenge is that modern applications now represent a diverse spectrum of workloads that span operational and analytical use cases. Each of these workloads need to scale seamlessly to meet demand.
This is just one of the many ways that you can benefit from SingleStore’s powerful simplicity.
SingleStoreOpens a new window creates a single global namespace for all of your data. Now, for example, you can seamlessly bring together your marketing data with your operational data. And you can combine spatial and relational searches with streaming data to alter pricing based on demand.
With SingleStore, it doesn’t matter if you have data on premises, in AWS, Google Cloud or Microsoft Azure. With SingleStore, you can use your structured, unstructured and semi-structured data wherever it is. At the same time, SingleStore enables you to abide by industry-specific or regional regulations that govern how data is handled and where it resides.
SingleStore also offers industry-leading performance in terms of speed. We have worked over the past decade to ensure extremely low latency. This positions our customers perfectly to address today’s data deluge and the growing volume of data that will arise as 5G becomes more widespread and adoption of demanding technologies like augmented reality takes hold.
These are the capabilities you need in a database as you move into 2021 and beyond.
IBM D2, Oracle and Teradata are struggling to remain relevant. While I’m proud of the early work I did innovating on Google BigQuery, it is not ideal for transactional workloads. Using multiple databases is not the best approach either. In discussing all of Amazon Web Services’ special-purpose databases at re:Invent 2016, AWS CEO Andy Jassy talked about â€œdatabase freedomOpens a new window .â€ Database freedom, he said, means choosing the right tool for the right job.
But you don’t need to incur the complexity and high overhead of an array of special-purpose databases to enjoy database freedom. You just need to achieve database speed and scalability as simply as possible. SingleStore allows you to do that.
That’s why now is the time for SingleStore.
SingleStore converges the transactional and analytical worlds, so you can understand what’s going on now and what has happened over time. With SingleStore, you enjoy high-performance concurrency and uniquely low latency. You can modify data after it’s been written with strong consistency.
Because you don’t have a lot of moving parts with SingleStore, you have fewer data management barriers and less overhead. You have lower analytics costs and can do more with more of your data. That gives you database simplicity, which allows you to achieve the speed and scale your organization needs.
SingleStore allows you to focus resources on using data to make more informed decisions and act in the moments the matter. That’s a win for your customers, constituents and organization.