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Exasol pledges to help customers avoid cloud bill shock with new DBaaS

Distributed in-memory system more efficient than other cloud data warehouses, vendor claims

Distributed in-memory analytics specialist Exasol has launched a database-as-a-service claiming its approach to parallel processing could help reduce nasty shocks in cloud fees.

According to the vendor, users buying the software-as-a-service get the ability to scale both vertically and horizontally while Exasol manages hot and cold data between the object store, local SSDs, and main memory. The back end is AWS, with which Exasol has a "deep technical partnership."

Launching a DBaaS is very much a "me too" move for a database firm. MariaDB, for example, launched SkySQL, a MySQL-derived system, in 2020. In analytics, Snowflake has long been a managed service.

Exasol was founded in Germany in 2000 and is used by Adidas, Olympus, and German retail giant Otto. Early use cases of its distributed, in-memory technology were based in-house and justified on the speed of query returns. For example, Berlin-based games company Wooga needed to rapidly calculate the median time spent in a game across 35 million users who might be logging in.

But CTO Mathias Golombek told The Register the same features that help with speed of query would help reduce costs in the cloud, which have been a problem with other cloud-based data warehouses.

"They grew from small installations, very often in the departments rather than the data warehouse teams, and then more and more was used and then if you really want to do some heavy lifting, and use it as your central data warehouse environment, it is incredibly expensive," he said. "The reason is that it needs a lot of infrastructure for a certain amount of performance and that's where Exasol is very strong. Through our in-memory, massively parallel processing (MPP) scalability, we leveraged infrastructure in a completely different way."

The problem of nasty shocks in cloud data warehouses has reared its head since Snowflake and AWS Redshift started gaining popularity. It is an argument longstanding on-prem specialist Teradata has used to convince users that its optimisation technologies help reduce costs with its cloud systems.

In September last year, one data warehousing insider told The Register that with on-prem Teradata, for example, "although the current system is a known finite capacity in terms of throughput, compute and storage, that is a guaranteed known cost. It's the unpredictability of the costs that are a big shock to people [using Snowflake] because not only can they not explain this month's bill, they've no idea what the next month's bill will be."

Exasol's Golombek said: "We think Snowflake is creating an amazing market for us in the future, where we can either replace it in some use cases or being used as the kind of consumption layer with Snowflake as the data lake."

Andy Hayler, CEO of analyst firm Information Difference, said costs were the most single most common complaint when companies move data warehousing to the cloud.

"It's a particularly highlighted problem with Snowflake partly because they are the big gorilla in the market, so there are currently a lot of people looking at the issue. And maybe they haven't done as good a job as they could have done in trying to help customers control costs," he told The Reg.

Exasol's approach made a lot of sense, he said. "It's certainly very efficient in using memory: it's a very elegant bit of architecture and riding the wave of that technology. Five or 10 years ago it would not be possible because memory was excruciatingly expensive. But Exasol is not the only approach [to controlling costs] by any stretch of the imagination."

It is Exasol's first major update for a while. In July 2020, it announced Exasol V7, touting support for GPUs and semi-structured data. The company floated on the Frankfurt Stock Exchange in May 2020. ®

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