Exasol Analytics Engine is a high-speed, in-memory, column-oriented analytics database designed to accelerate business intelligence, reporting, and data science workloads. It supports flexible deployment models, including on-premises, cloud, and hybrid environments, and integrates easily with existing data stacks and BI tools. Exasol enables organizations to process complex queries and large data volumes rapidly, supporting advanced analytics and machine learning directly within the database engine.

Key Features

In-memory, columnar architecture Accelerates analytics by storing and processing data in-memory using a column-oriented approach.

• Massively Parallel Processing (MPP) for high concurrency and speed
• Efficient compression and automatic self-optimization

Flexible deployment Supports on-premises, cloud, SaaS, and hybrid setups.

• Seamless integration with existing tech stacks
• No need for data migration or rip-and-replace

Advanced analytics and machine learning Enables in-database analytics and operationalization of ML models.

• Built-in support for Python, R, Java, and Lua UDFs
• Exasol AI Lab for streamlined AI model integration and deployment

Automatic tuning and management Reduces manual administration and performance tuning.

• Self-optimizing with automatic indexing and statistics
• Cluster management with failover and scaling

Integration with BI and data tools Connects with popular BI platforms and data ecosystems.

• Supports ODBC, JDBC, ADO.NET, MDX, and virtual schema technology
• Real-time analytics and reporting capabilities

Benefits

Performance and scalability Delivers rapid query performance and scales for large, complex data workloads.

• Up to 20x faster processing than other analytics databases
• Handles high concurrency and large datasets efficiently

Cost efficiency Optimizes infrastructure usage and reduces total cost of ownership.

• Superior price/performance ratio, reducing hardware and licensing costs
• 320% ROI through savings in implementation, maintenance, and training

Flexibility and future-proofing Adapts to changing business needs and technology environments.

• Deploy anywhere: on-premises, cloud, or hybrid
• Integrates with existing BI tools and data pipelines without disruption