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The taxi journey continues

After the release of MonetDB/e Python, which brought the power of MonetDB data analytics to the world of Python embedded databases, we set out to expand its reach to the Java environment. Our goal is to provide a lightweight, full-featured embedded database that harnesses MonetDB’s columnar analytics power while keeping the familiar JDBC interface. The power of a full-fledged database server at your fingertips as an embeddable library.

MonetDB/e: an embedded analytical SQL engine on Windows

With the release of MonetDB/e, we have a new member in the family of embedded DBMSs on Windows optimised for data analytics. How does it compare to some long term members in this family, e.g. SQLite3 and Microsoft SQLserver Express? Let’s take MonetDB/e on another quick trip with the NYC taxi benchmark as demonstrated in a Linux setting before.

Taking MonetDB/e for a taxi ride

In this article, we illustrate the performance potential of MonetDB/e for data analytics with the NYC Taxi benchmark.

The MonetDB/e Python interface for data analytics

We made the MonetDB/e functionality available as a simple drop-in library in Python 3 with a Python/SQLite3 compatible interface to smooth its adoption by users of embedded DBMS.

MonetDB/e, a mature embedded SQL DBMS

We introduce MonetDB/e, our new full-fledged embedded DBMS for data analytics. It encapsulates the full SQL functionality offered by MonetDB, including a rich collection of data types, triggers, schema management, and persistent stored modules.
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