Cloud data warehouses · Exasol AG

Exasol

In-memory, massively parallel analytics database available as a managed cloud service or self-hosted software.

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Exasol is a columnar, in-memory analytics database built for high-performance SQL analytics on large datasets. Its massively parallel processing engine automatically indexes and compresses data without manual tuning, which the vendor positions as a differentiator against warehouses that require ongoing index or partition management. Exasol is offered as a managed service on AWS and Azure (Exasol SaaS), as self-managed software customers can run on their own infrastructure or Kubernetes, and as a free single-node Community Edition for smaller workloads. It targets analytics and data science teams running complex, ad hoc SQL against large fact tables, and competes with Vertica, Snowflake, and Teradata in performance-sensitive enterprise analytics.

At a glance

Vendor Exasol AG
Pricing model Quote only
Free tier Yes
Deployment Cloud, Self-hosted
Open source No
Best for Analytics teams running complex, ad hoc SQL who want strong price/performance without manual index tuning.

Pricing

Licensed by capacity (historically RAM-based) with SaaS, self-managed, and a free Community Edition; the public pricing page does not publish figures and directs prospects to a free trial or sales contact.

Checked on the vendor's own page on September 21, 2026: no prices are published. Expect to be quoted.

Features

  • In-memory columnar storage with automatic compression
  • Massively parallel processing with automatic, self-tuning indexing
  • SaaS, self-managed, and on-premises deployment options
  • In-database machine learning via Python, R, and Java UDFs
  • Virtual schemas for federated queries into other databases
  • Free single-node Community Edition for evaluation and small workloads
  • ACID-compliant transactional consistency

Integrations

Profile last reviewed September 21, 2026

Alternatives

OpenText Vertica Columnar MPP analytics database, now owned by OpenText, deployable on-premises, in Kubernetes, or across major clouds. Teradata VantageCloud Teradata's cloud-delivered evolution of its enterprise MPP data warehouse, unified under a single Teradata Unit pricing currency. Greenplum Open-source, massively parallel PostgreSQL-based data warehouse for large-scale analytical SQL.

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Terms to know

Data warehouse A centralized, structured database optimized for fast historical reporting rather than day-to-day transactions. OLAP (online analytical processing) A category of technology optimized for fast, multi-dimensional aggregation and slicing of data for analysis. Machine learning Building models that learn patterns from data to make predictions or decisions, rather than following hand-coded rules. Columnar storage A file and database layout that stores each column's values together, instead of storing each row together. Massively parallel processing An architecture that splits a query across many independent compute nodes, each processing its own data slice.

Related guides

How to choose a cloud data warehouse Start from your cloud, your pricing tolerance and your workload shape — general BI, high-concurrency apps, or enterprise mixed workloads — not the feature list.