A compression-focused database technology

When talking about compression, typical databases always treat it as a way to save storage space and lower costs, since many vendors treat storage and computing as separate pricing. Under that point of view, as we compress more than any other solution in the market, we can offer the simplest and cheapest price of all. We take it further because we compress so much that it becomes the key factor in our performance benchmarks - data is so reduced that we can cache a lot more of it in RAM, getting much better performance from the same commodity hardware. This is totally truth and possible due to SlicingDice's secret sauce: S1Search.

S1Search is a Java-based low-latency zero-garbage database technology built from scratch by our team, that heavily focus on mastering a single thing, data compression. That's the reason compression ratios between 1/15 and even 1/30 of the original data size are common in S1Search. The logic here is pretty simple: as we can store data using just a fraction of its original size, we can offer you a query speed commitment, as most of your data resides in RAM memory and CPU cache all the time.

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Why is data compression so powerful?

See how data compression can strongly impact on our pricing and query speed.

More Compression = Less Storage Costs = Lower Prices

Data compression is one of the parts where our developers have put a huge amount of time and effort. Because of that, it’s common for us to see compression ratio between 1/10 and even 1/30 of the original data size when inserting it on S1Search.

There is no magic about what we do and the logic is pretty straightforward: as we can store our customer's data using just a fraction of its original size, it cost us much less than any other solution, so we can be much more aggressive on pricing.

Due the economy of scale, the more customers we get, more S1Search servers we add, making our average storage cost even lower, consequently allowing us to decrease our prices.

More Compression = Less I/O = Faster Queries

A known fact regarding primary memory and storage devices is that access to the former is around 1 million times faster than to the latter when considering hard drives and 10 thousand times faster when considering modern SSDs.

Therefore, efforts to reduce the amount of data transferred to and from disks are usually worth the price — and this is precisely the point of compressing data. At the cost of adding CPU cycles to compress and uncompress data, huge gains on the size of transferred data can be achieved by setting a proper compression scheme. But one scheme won’t fit them all.

Since every type of data has its own characteristics, different compression protocols might be required to achieve optimal compression rates, and we’ve implemented a many of them on S1Search.

SlicingDice's Database Capabilities


It's not only about compression. It's also about freedom, security and consistency.

Schema freedom.

Don't worry about schema definition.

The database technology created by SlicingDice is designed to be almost schemaless. By schemaless, we mean a way to organize data that’s so flexible it feels like there is no schema at all, so you won’t have to plan in advance how to use data in the future, as you can reorganize dimensions and columns on demand. Also, you can store data with a varied structure and query it normally, which is ideal for massive and heterogeneous datasets.



Secure by design.

Any data is encrypted by default.

We take security to the next level by leveraging our proprietary encryption method, native to our database technology. This means that in the rare occurrence of unauthorized access, the stored data will be in binary, hashed format, and no one will be able to guess what's inside the files. SlicingDice clearly understands that security is the basis of a data warehouse offering as a service, so organizations can treat their data as an asset that is private and secure, being able to deliver this value onto their own customers, in turn becoming more trustworthy and valuable for them.



Exact results, not approximations.

Queries always return exact results by default.

We want anyone to be free to leverage data according to their needs, and not according to technical or financial limitations. By querying the whole dataset, we ensure query results are as accurate as possible. By supporting approximations, we ensure organizations can leverage data in anyway required. We allow for both possibilities without changing our 10-seconds query speed commitment. Insert and query as much data as you need, with maximum accuracy without worrying about paying more to use your data.



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