Exasol is the high-performance, in-memory massively parallel processing (MPP) database specifically designed for analytics. From business-critical data applications to advanced analytics, Exasol helps you analyze large volumes of data faster than ever before, helping you to accelerate your BI and reporting, and to turn data into value.
Key Features and Benefits
In-memory technology - Innovative in-memory algorithms enable large amounts of data to be processed in the main memory for dramatically faster access times.
Column-based storage and compression - Columnar storage and compression reduces the number of I/O operations and amount of data needed for processing in main memory and accelerates analytical performance.
Massively Parallel Processing (MPP) - Exasol was developed as a parallel system based on a shared-nothing architecture. Queries are distributed across all nodes in a cluster using optimized, parallel algorithms that process data locally in each node’s main memory.
High user concurrency - Thousands of users can simultaneously access and analyze large amounts of data without compromising query performance.
Scalability - Linear scalability lets you to extend your system and increase performance by adding additional nodes.
Self-tuning - Intelligent algorithms monitor usage and perform self-tuning tasks automatically, which optimize performance and minimize any data administration overhead.
Comprehensive support for Hadoop - Hadoop integration has never been so easy. Exasol supports all native HDFS formats enabling you to perform high-speed analytics against structured and unstructured data faster and easier.
Faster access to more data sources - Through a data virtualization framework called “virtual schemas” as well as a high performance data integration framework, you can connect to and analyze data from more sources than ever before.
Advanced in-database analytics - Alongside out-of-the-box support for R, Python, Java and Lua, Exasol allows you to integrate the analytics programming language of your choice and use it for in-database analytics.
Unrivalled connectivity - Exasol supports standard interfaces for integrating upstream and downstream (BI) tools. The standard interfaces that ship with the Exasol software include ODBC, JDBC, ADO.NET. You can easily integrate Exasol with BI Tools and Data Integration tools from all the leading vendors, such as - Informatica, Talend, Pentaho, Tableau, Business Objects, Cognos, and Microstrategy. You can also easily connect to Exasol using popular SQL clients such as DBVisualizer, DBeaver.
Flexible Deployment Options - Exasol’s flexible architecture provides a variety of deployment options. Choose the platform that best fits the needs of your business: as a software-only solution, as an appliance, or in the cloud.
Standardized SQL - Exasol supports ANSI standard SQL 2008 (including all analytical functions) as well as a large selection of the commonly-used Oracle SQL dialect. Its support of parts of Oracle SQL language set is of particular benefit when migrating from Oracle-based applications. There is a minimal need to re-write or change the code.
Automation - Exasol has high degrees of automation built into its design to ensure that it delivers high performance with minimal need for expensive DBA resource to operate it. Some of the key areas of automation are:
Automatic distribution of data - evenly distributes data across all servers in the cluster.
Automatic duplication of data - automatically duplicates data across servers to ensure data integrity in the event of a server failure.
Automatic selection of compression algorithms - Exasol automatically selects the compression algorithms that are data type-specific and optimized for in-memory processing. These algorithms also work independently on each node to ensure optimal performance.
Automatic compression of data - Data is compressed at column-level with identical images stored in the main memory and on persistent media (hard disk) to optimize performance.
Automatic monitoring and logging of system resources - Exasol monitors system resources such as RAM, Disk, CPU to aid in capacity planning.