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Exasol SaaS Natively Interfaces with Keboola

May 4, 2022

Exasol SaaS – the scalable, consumption-based SaaS database based on Amazon Web Services (AWS) – now natively interfaces with Keboola, a cloud-based Data Stack as a Service platform. Keboola provides the first complete solution for data engineers, data analysts, and analytics engineers to deliver on the full spectrum of data demands – from data ingestion to automation. Users will benefit from a built-in function that connects them directly to Keboola from Exasol’s SaaS interface. The Keboola low-code platform provides more than 250 integrations for building ETL/ELT and other pipelines, automation, one-click workflows with integrated business case templates, as well as enterprise grade data governance over the entire stack. It’s a combination that provides improved data accuracy and reduces the time to value.

Commenting on the news, Milan Veverka, VP of Alliances at Keboola said: “We believe that by surrounding ourselves with amazing people, we can achieve anything. That's why we focus on building partnerships that matter. Partnerships with companies that have a similar mindset as we do - empowering everyone to make data-driven decisions. Keboola and Exasol provide great solutions together. We built a simple to use, cost-effective and easy to maintain Data Stack as a Service while Exasol provides its fast in-memory database that helps customers to get to their solution. Together we will make both the implementation and the queries themselves much faster for shared customers.”

In addition to the new collaboration with Keboola, Exasol has introduced a series of new product capabilities that expand on its fully managed, SaaS offering. The new product capabilities will further enhance a customer’s ability to access data-led insights quickly, without needing to manage hardware infrastructures.

These innovations include:

Enhanced AI/ML capabilities: Customers can now solve complex analytics challenges with ease, such as predictive analytics, by bringing in AI/ML algorithms directly to the data. Operationalizing ML models will also bring maximum performance within the database to its users.

Data virtualization support: Analysts will be able to access objects from external sources without the need for migrating data. This support will also eliminate the need for the costly management of duplicate data. It will allow users to more easily access their data – whether it’s stored locally or in the cloud – and set-up or create a logical data warehouse.

Amazon SageMaker extension: Exasol SaaS now supports a SageMaker Extension, enabling users to develop end-to-end machine learning projects on data stored in Exasol using the Amazon SageMaker Autopilot service. Doing so mean users can turn data into actionable insights in a matter of minutes.

“When it comes to an organization’s data strategy, data leaders are looking for the confidence to modernize with market-proven, enterprise capabilities that offer flexible migration paths – often to the cloud – at a pace and time that fits with budget and resource constraints,” says Donald Kaye, Chief Commercial Officer at Exasol. The impact of this decision can be profound: affecting costs, the pace of innovation, production releases, marketing penetration and security, to name just a few. “To address the complex challenges organizations face when looking to garner actionable insight from their data, we announced, in February, the strengthening of our hybrid cloud proposition by making our high-performance analytics database available via Exasol SaaS.”

Exasol SaaS is available in two versions. The Exasol SaaS Standard Edition delivers industry leading performance on-demand for organizations with smaller data volumes who don’t require advanced analytics and data integration features or extended support. The Exasol SaaS Enterprise Edition is designed for organizations that require multi-departmental analytics environments, need to perform ML or AI in the database, or have complex requirements in terms of data integration and data virtualization.

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