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We share Squerall a software for querying large and heterogeneous data

From: Mohamed Nadjib Mami <mami@iai.uni-bonn.de>
Date: Tue, 14 May 2019 17:26:59 +0200
Message-ID: <91b74c17458213d69ea7a56d95b9c3d9.squirrel@webmail.iai.uni-bonn.de>
To: semantic-web@w3.org
Cc: damien.graux@iais.fraunhofer.de, scerri@cs.uni-bonn.de, jabeen@cs.uni-bonn.de, auer@l3s.de
Dear Semantic Webbers,

We are glad to share with you Squerall [1,2] v0.2, a software solution
implementing the so-called Semantic Data Lake. It allows the uniform
querying of heterogeneous and large data directly where it is stored,
without prior data materialization of transformation. Squerall implements
a virtual ontology-based data integration whereby data schemata are mapped
to ontology terms creating a semantic middleware, which is then queried
using SPARQL.

Squerall (from Semantic QUERy ALL) uses two popular query engines for
large scale query execution: Apache Spark and Presto. It uses RML and FnO
for mapping creation. It supports out-of-the-box several data sources,
from CSV to Parquet to so called NoSQL stores e.g. MongoDB and Cassandra
(but also Couchbase and Elasticsearch, experimentally). It is built from
the ground-up with extensibility in mind [3]; more data sources can be
'programmatically' supported with minimal effort and other query engines
can be integrated (e.g., Alluxo, Drill, Impala).

Finally, Squerall comes with a GUI [4] allowing to connect to the data,
create mappings from data schemata, and guide non-SPARQL experts build
correct and supported [5] queries.

We will be happy to help anyone wanting to try it out, and even more
happier, in case someone would like to deploy it in a real use-case.
Contact channels are provided for that purpose, or for any general

Kind regards,
Mohamed Nadjib Mami
Fraunhofer IAIS & Bonn University

PS: for those among you who will be attending The WebConf, please come by
to our poster session scheduled on Wednesday 14:00 for a real demonstrator
[2] of Squerall.

[1] [Squerall | Query heterogeneous big data using one query
[2] [Querying Data Lakes Using Spark and
[3] [Extending Squerall · EIS-Bonn/Squerall Wiki ·
[4] [GitHub - EIS-Bonn/Squerall-GUI: The user interface of Squerall
[5] [Squerall Basics · EIS-Bonn/Squerall Wiki ·
Received on Tuesday, 14 May 2019 15:48:06 UTC

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