MonetDB is a column-oriented relational database management system (RDBMS).
It is designed to provide high performance on complex queries against large databases, such as combining tables with hundreds of columns and millions of rows.
MonetDB is the focus of database research pushing the technology envelop in many areas. Its three-level software stack, comprised of SQL front-end, tactical-optimizers, and columnar abstract-machine kernel, provide a flexible environment to customize it many different ways. A rich collection of linked-in libraries provide functionality for temporal data types, geometry data types, math routine, JSON, URL and UUID data types, User Defined Functions (UDFs) written in Python, R or C/C++. In-depth information on the technical innovations in the design and implementation of MonetDB can be found in our science library.
This is free and open source software.
Key Features
- SQL compliant database interface, enabling applications ranging from pure analytics to hybrid transactional/analytical processing.
- It supports common features including keys, joins, views, triggers, and stored procedures, along with full-ACID properties for concurrent transactions. Additionally, MonetDB embraces advanced SQL standards such as SQL:1999 ROLLUP CUBE, and GROUPING SETS, SQL:2003 merge statements, and SQL:2011 window functions, ensuring comprehensive tools for database management and analytics.
- Delivers query results in mere seconds or even less. This high-performance on heavy analytical workloads is achieved through fine-grained optimization across the database software stack.
- Leverage hooks to integrate your own user-defined functions (UDFs) in SQL. This flexibility is complemented by support for a variety of UDF types, including aggregate, filter, window, and table returning SQL functions.
- Cross-platform support – runs under Linux, macOS, and Windows.
Website: www.monetdb.org
Support:
Developer: MonetDB Foundation
License: Mozilla Public License Version 2.0
MonetDB is written in C. Learn C with our recommended free books and free tutorials.
Related Software
| Column-Oriented Databases | |
|---|---|
| MariaDB ColumnStore | Uses a massively parallel distributed data architecture |
| DuckDB | In-process SQL OLAP database management system |
| Druid | High performance, real-time analytics database |
| Databend | Cloud data warehouse |
| ClickHouse | Real-time analytics database management system |
| InfluxDB Core | Scalable datastore for metrics, events, and real-time analytics |
| Doris | Modern data warehouse for real-time analytics |
| VictoriaMetrics | Scalable solution for monitoring and managing time series data |
| StarRocks | High-performance analytical database |
| MonetDB | High performance relational database system for analytics |
| Kudu | Distributed data storage engine |
| Pinot | Real-time analytics platform |
| CrateDB | Distributed SQL database management |
Read our verdict in the software roundup.
| Relational Databases | |
|---|---|
| MariaDB | Seeks high compatibility with MySQL, ensuring drop-in replacement capability |
| PostgreSQL | Award winning Object-relational database management system |
| MySQL | Multithreaded, multi-user SQL database management system |
| SQLite | Embeddable SQL Database Engine |
| rqlite | Distributed database built on SQLite |
| MonetDB | High performance relational database system for analytics |
| Firebird | Relational database offering many ANSI SQL features |
| H2 | Relational database management system written in Java |
| HSQLDB | JDBC interface, client-server version, query tool, grid and more |
| CUBRID | Database engine with built-in enterprise grade features |
| Virtuoso | Data Management with Web Application Server and Web Services Platform |
| Apache Derby | Full-featured relational database implemented entirely in Java |
Read our verdict in the software roundup.
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