Exasol is a technology provider with headquarters in Nuremberg, Germany, which was founded in 2000. Today, the company operates mainly in Europe and the United States. The majority of its customers are from German-speaking countries. However, approximately 15 percent of total sales are generated in the United States, with a strong upward trend.
Exasol is leveraged and has been operating profitably for 5 years. The company went public in May 2020. Organizations of various sizes and industries use Exasol, which has a broad network of implementation and technology partners. In addition to its partners, Exasol works closely with its community, which develops the integration capabilities of the database based on a free open source version of the Exasol database on GitHub. Developments from the community are moderated and reviewed by a dedicated dev team.
Exasol offers a relational, column-based, MPP-enabled, in-memory database – an analytical database on Exasol’s own infrastructure. Exasol sees itself as the highest-performing database for analytical workloads and proves this with TPC-H benchmarks. Some customers leverage Exasol as an accelerator for BI or analytics, but a growing number have modernized their central legacy data warehouse by switching completely to Exasol. Using Exasol as a logical data platform with a central access layer is the next step, and this also offers the capability to provide BI users with access to data science models in any language through Exasol’s data science integration.
The database can be deployed in the public cloud, but also on-premises or in a hybrid setup. It can be operated in AWS, Google and Microsoft Azure environments and can use their infrastructure for backups, for example. Customers have the flexibility to operate Exasol on their own (e.g., for GDPR reasons), but they can also let Exasol run the system as a fully managed service for them. A full version of the database is also available for free as a Community Edition (limited to 200GB of raw data).
The database itself is characterized above all by its high query performance, self-optimization algorithms and a plug-in concept that simplifies the integration and functional expansion of the database.
Self-tuning or self-optimization has been on the feature list of the database since day one and is constantly being developed. To ensure high performance for current workloads, algorithms monitor database usage as well as keeping the organization of data optimized. This automation is a core function and added value of the database, and it means that few manual configuration options are available for the database.
User & Use Cases
93 percent of survey respondents use the database for data warehousing and BI, while 69 percent use it for data integration. Exasol itself does not offer any functions for augmented data integration. However, the database technology is used to provide integrated views on data and data can be loaded into the database in parallel. 66 percent use Exasol as a data platform. The database is no longer used for BI workloads alone. Users see it as a database for further analytical use cases. It is interesting that 62 percent say they use it for self-service analytics. Exasol is a very technical tool with no business-user-friendly interfaces for performing evaluations. A possible explanation for this finding is that technically experienced users can quickly build up data in an Exasol-based sandbox for self-service analyses. We expect to see a higher frquency of this use case with the increasing use of cloud services.
However, the customers taking part in this survey were all using the on-premises variant. It is not easy to explain why one third of respondents claimed to be using Exasol for data warehouse automation. Exasol supports modeling paradigms such as Data Vault, which favor automation. However, the automated creation of data models and loading of tables is not part of the functional scope of the database and has to be performed using specialist tools. It may be that customers are referring to the automated performance optimization (e.g., creation of indices) offered by Exasol.
Companies of all sizes use Exasol. Against this background, the average number of users does not appear to be particularly high, with a mean of 269 and a median of 65. However, the mean number of 17 technical users (and median of 10) is surprisingly high given Exasol’s claim that database tuning is done automatically.
Current use
n=29
Number of users using Exasol Database
n=29
Number of technical users using Exasol Database
n=29
Company size (number of employees)
n=29
Summary of Exasol Database highlights
Exasol achieved 18 top rankings and 4 leadership positions in its two peer groups in The Data Management Survey 20. This is an outstanding result and a ringing endorsement from Exasol users. All respondents to this survey stated that they would recommend Exasol’s high-performance database technology without reservation. Exceptional results in the ‘Performance’ and ‘Platform stability’ KPIs were particularly convincing. Exasol describes itself as the best performing database for analytical workloads. Participants in this survey clearly agree. Also worthy of mention is Exasol’s support – rated at 9.9/10 – which shows that the vendor has a dedicated team committed to solving customer scenarios.
Performance – Top-ranked
Peer Group: Data warehouse technologies
Platform reliability – Top-ranked
Peer Group: Analytical database products
Price-to-value – Top-ranked
Peer Group: Analytical database products
Recommendation – Top-ranked
Peer Group: Analytical database products
Support quality – Top-ranked
Peer Group: Data warehouse technologies
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BARC’s Vendor Performance Summary contains an overview of The Data Management Survey results based on feedback from Exasol Database users, accompanied by expert analyst commentary.
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