SlicingDice Documentation

SlicingDice - The All-in-One Solution Documentation

Welcome to the SlicingDice documentation. You'll find comprehensive guides and documentation to help you start working with SlicingDice as quickly as possible, as well as support if you get stuck. Let's jump right in!

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What SlicingDice is good at

In this section, we're going to talk about use cases in which SlicingDice truly excels. If your use case is similar to these, we might be a good fit for you.

Analytics queries correlating many columns, where relational databases are too slow

Usually, relational databases struggle with queries that JOIN many tables. Our state-of-the-art database engine allows anyone to run queries with multiple columns and receive the results really fast. As an example, SlicingDice can find out in under 10 seconds which users accessed sports, news and video-games pages more than 5 times in the last week, even if your website is accessed by millions of users every day.

Big data applications

From day 1, SlicingDice was built to handle billions of rows and thousands of queries without bottlenecks. For applications with large data volumes, SlicingDice will be much faster than well-known relational or NoSQL databases.

Organizations that don't want an entire team to just manage data infrastructure

Our serverless solution ensure you don't need to worry about any maintenance. In any size organizations this can save a lot of time and money, which can be better applied in more critical tasks.

Applications where the amount of data is much larger than the number of columns

Since one of our pricing models is based on the number of columns of your database (pay-per-column), you're able to store and query data in a pretty cost-effective way, since it's a fixed pricing, for an unlimited number of rows. For example, industries placing sensors and other Internet of Things devices in their factories won't be charged by the amount of data they send to SlicingDice, but by how many metrics they measure.

Large amounts of temporal data

SlicingDice is perfect for cases that use time series data. It was built to support this data type in parallel with every other data type, enabling organizations to store and query time series and non-time series data *in the same database. For instance, you might be interested in monitoring your servers and check their performance and stability in near-real-time. To achieve that, you need to store every server metric produced in the last 24 hours and check the average performance and possible outliers.

When you don't want to have a server only to run databases

You don't need to invest in expensive hardware or cloud servers just to store your database. SlicingDice allows you to simply register, create a database and start leveraging data. This is useful for any project.

Nevertheless, no database is able to fit every possible use case on Earth, neither does SlicingDice.
Check our section on current SlicingDice restrictions to understand what we don't support yet (but be sure we're working hard to overcome these limitations). If you need special arrangements, simply contact us.

Still not sure if SlicingDice is a good fit for your needs? Talk to our developers right now.

What SlicingDice is good at

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