Exasol review
A hybrid MPP warehouse for demanding analytics, lakehouse queries, streaming, and in-database ML.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Exasol is an in-memory, massively parallel analytics database for data warehousing, business intelligence, lakehouse acceleration, and AI/ML workloads. It is aimed at data teams, developers, and enterprises handling demanding analytical workloads across fully managed SaaS, hybrid, cloud, and on-premises deployments. Its focus on high concurrency, SQL analytics, and scalable clusters makes it a fit for hybrid analytics teams that need both warehouse performance and broader data-platform connectivity.
Pricing is organized around monthly pay-as-you-go cluster sizes. XS costs $3.30 per hour with 8 vCPUs and 64 GB memory; S costs $6.60 with 16 vCPUs and 128 GB; M costs $13.20 with 32 vCPUs and 256 GB; L costs $26.40 with 64 vCPUs and 512 GB; XL costs $52.80 with 128 vCPUs and 1024 GB; 2XL costs $105.60 with 256 vCPUs and 2048 GB; and 3XL costs $158.40 with 384 vCPUs and 3072 GB. Storage is separate at $25 per TB per month. A free plan and 30-day trial add entry points, while pre-purchase pricing is available by sales quote. Teams should budget for storage independently from compute.
The platform fits established analytics ecosystems through Tableau, Power BI, Looker, dbt, Spark, JDBC, ODBC, Python, and R. Data movement options include Apache Kafka, Amazon Kinesis Data Streams, Amazon S3, Azure Data Factory, and AWS Glue, while lakehouse querying supports Amazon S3 and Azure Data Lake Storage. In-database Python, R, and Java machine-learning models extend the warehouse beyond reporting. Exasol is a strong choice for organizations that need concurrency, deployment flexibility, streaming ingestion, and integrated analytical workloads. Organizations requiring an open-source warehouse, or a simpler pricing structure with storage bundled into compute, should consider alternatives instead.
Exasol pros and cons
- Where it wins
- High-concurrency in-memory massively parallel processing
- Separate storage and compute with cluster scaling
- Lakehouse, Kafka, BI, and in-database ML support
- Where it doesn't
- Storage is priced separately from compute
- No open-source deployment option
- Pre-purchase pricing requires a sales quote
Exasol fact sheet, pricing and score →
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