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Amos II

Uppsala DataBase Laboratory

Welcome to Uppsala DataBase Laboratory (UDBL). We are a research group in the Department of Information Technology at Uppsala University, Sweden.

The research direction of the group concentrates on developing methods for scalable and extensible processing of queries analyzing different kinds of distributed data in terms of semantic 'NoSQL' data representations. Of particular interest is scalable processing of high level queries analyzing high volume data streams. A challenge is to provide scalable processing as the data volume increases and the analyzes become increasingly costly. Our approach is to develop smart query transformation techniques and distributed  execution strategies in an extensible platform where external systems, algorithms, and data managers can be plugged-in.

Our research system Amos II provides a platform for scalable processing of queries to many different kinds of heterogeneous data sources. The queries are expressed in terms of a high level semantic data model. The system enables integration of external storage managers, databases, and computational systems though APIs in several programming languages.

In SCSQ and its successor SVALI Amos II has been generalized for scalable parallel processing of queries to high volume data streams involving expensive computations.

Run the Linear Road Benchmark simulation of a toll expressway system on your notebook: SCSQ-LR. Our massively parallel implementation of the Linear Road Benchmark SCSQL-PLR has the highest published performance.

Watch Google Tech Talk presenting our scalable compute intensive data stream analythics technology.

The start-up company Stream Analyze develops technology for scalable on-line analyses of streamed data based on our research.

In SAQ the query processor is extended to provide flexible and scalable preservation and querying of relational databases using the standard semantic web query language SPARQL.

SciSPARQL uses the Amos II platform to provide processing of queries combining numeric data and meta-data by extending SPARQL with array capabilities.



We are responsible for the Doctoral study subject area on Computer Science with specialization in Database Technology, TNDAVE04. There is a doctoral study plan in Swedish or English. We are teaching doctoral student level courses on modern database technology within the programme.

For the undergraduate education we are responsible for courses in Database Design and Data Mining.  We have co-authored the Swedish textbook on database technology: Databasteknik

Looking for MSc project on modern database technology? Contact Tore Risch.


We participate in SMART VORTEX, a Large Integrated Project co-financed by the European Union within the Seventh Framework Programme. The goal of the project is to provide a technological infrastructure consisting of a comprehensive suite of interoperable tools, services, and methods for intelligent management and analysis of massive data streams to achieve better collaboration and decision making in industrial product life cycles. The project is a collaboration between a number of European universities and industrial partners. In the project we have developed the general platform SVALI for scalable parallel processing of high volume data streams involving expensive computations.

We participate in eSSENCE, a Swedish e-science research collaboration to create a research environment where the interplay between different e-science competences will open up the field for novel applications, more realistic simulations, and new scientific solutions, models and methods.

The goal of the project Scalable search of product life cycle information (SSPI)  with support from SSF is to produce (1) novel methods for scalable search in high volume data streams, (2) novel scalable methods to verify systems based on data stream management system (DSMS) technology, (3) novel searchable semantic web based models to preserve product data, and (4) novel ways to verify the functioning of products in use.  

Finished projects

We organized EDBT: 14th International Conference on Extending Database Technology, and ICDT: 14th International Conference on Database Theory, March 21-25, 2011.

In the iStreams project (supported by Vinnova and ASTRON) we developed SCSQ (SuperComputer Stream Query processor), a Data Stream Management System (DSMS) to process very high volume data streams. SCSQ runs in a massively parallel and heterogeneous computing environment containing Linux clusters and an IBM BlueGene computer. SCSQ executes data stream queries that filter, transform, and join data from receivers of low frequence space radio signals.

In the GSDM project (supported by Vinnova) we developed a stream database query manager for high volume queries. This project was in cooperation with IRFU and ASTRON.

In the POQSEC Project (supported by VR) we developed a scalable and distributed query processor utilizing the peer-oriented GRID infrastructure NorduGRID. This project was an UPPMAX project.

Within the EU project Advanced eGovernment Information Service Bus we developed scalable methods to search wrapped eGovernment virtual repositories in terms of semantic web representations and queries. The RDFViewer system enables encapsulating (wrapping) different kinds of data sources to make them available for semantic web tools to query using the query languages SparQL, RDQL, or SQL.The SWARD (Semantic Web Abridged Relational Databases) subsystem wraps relational databases according to some ontology and SWATM (Semantic Web Abridged Topic Maps) wraps Topic Map data. 

We participated in the project Personalized Access to Distributed Learning Repositories (PADLR) which was part of the Wallenberg global learning network research program on distributed collaborative learning innovations. Within PADLR we developed PSELO, a semantic web based query processing system for searching learning material from a peer-to-peer based educational infrastructure.

We collaborated with formerly Alzato Inc. in the development leading to the product MySQL Cluster, which is based on the PhD Thesis here.

How to find us:   Uppsala map        Uppsala right now!

© 2007 Uppsala Universitet, Department of Information Technology, Box 337, 751 05 Uppsala, Sweden | This page is maintained by Tore Risch