Frequently Asked Questions

General

Connectivity

timbr supports both JDBC and ODBC. We reuse the thrift-server protocol of Apache Hive and Spark. This means you can connect to timbr’s Knowledge Graph using Hive/Spark JDBC/ODBC drivers (in most BI tools they already come embedded, so no installation needed).

Category: Connectivity

Creating an ontology: You can either use our Visual Ontology Modeler (no SQL needed) or use timbr extended SQL DDL statements.

Mapping data to the ontology: You can either use our Visual Ontology Data Mapper (no SQL needed) or use timbr’s extended SQL DDL statements.

Querying the Knowledge Graph: SQL, Python/R, dataframes, and natively in Apache Spark (SQL, Python, R, Java, Scala). GraphQL can be supported by integrating external open source projects that support the translation of GraphQL to SQL.

Category: Connectivity

Yes, GraphQL is supported by integrating external open source projects that support the translation of GraphQL to SQL.

Category: Connectivity

timbr supports query of JSON and XML using Apache Spark.

Category: Connectivity

Yes, this could be generated easily (creating the SQL DDL statements of timbr directly from the XML hierarchy/relationships).

Category: Connectivity

Yes, moving from SPARQL to timbr’s simplified SQL is quite trivial and easy to do.

Category: Connectivity

Yes, timbr works extensively with SQLAlchemy. Another valid option for python users is DataFrames.

Category: Connectivity

Yes, timbr is compatible with OWL-DL and some OWL-2 inferences.
If there is a clear business value to add more OWL-2 inferences, we can support them as well. timbr’s inference engine is based on query-rewriting techniques. If timbr encounters slow queries/performance, timbr can specifically materialize the part of knowledge that is required.

Category: Connectivity

yes.

Category: Connectivity

This is supported as part of our integration with Apache Spark/Apache Hive: https://github.com/awslabs/emr-dynamodb-connector
I a direct connection is needed we can use Simba Amazon DynamoDB ODBC and JDBC Drivers.

Category: Connectivity

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Connectivity

Connectivity

timbr supports both JDBC and ODBC. We reuse the thrift-server protocol of Apache Hive and Spark. This means you can connect to timbr’s Knowledge Graph using Hive/Spark JDBC/ODBC drivers (in most BI tools they already come embedded, so no installation needed).

Category: Connectivity

Creating an ontology: You can either use our Visual Ontology Modeler (no SQL needed) or use timbr extended SQL DDL statements.

Mapping data to the ontology: You can either use our Visual Ontology Data Mapper (no SQL needed) or use timbr’s extended SQL DDL statements.

Querying the Knowledge Graph: SQL, Python/R, dataframes, and natively in Apache Spark (SQL, Python, R, Java, Scala). GraphQL can be supported by integrating external open source projects that support the translation of GraphQL to SQL.

Category: Connectivity

Yes, GraphQL is supported by integrating external open source projects that support the translation of GraphQL to SQL.

Category: Connectivity

timbr supports query of JSON and XML using Apache Spark.

Category: Connectivity

Yes, this could be generated easily (creating the SQL DDL statements of timbr directly from the XML hierarchy/relationships).

Category: Connectivity

Yes, moving from SPARQL to timbr’s simplified SQL is quite trivial and easy to do.

Category: Connectivity

Yes, timbr works extensively with SQLAlchemy. Another valid option for python users is DataFrames.

Category: Connectivity

Yes, timbr is compatible with OWL-DL and some OWL-2 inferences.
If there is a clear business value to add more OWL-2 inferences, we can support them as well. timbr’s inference engine is based on query-rewriting techniques. If timbr encounters slow queries/performance, timbr can specifically materialize the part of knowledge that is required.

Category: Connectivity

yes.

Category: Connectivity

This is supported as part of our integration with Apache Spark/Apache Hive: https://github.com/awslabs/emr-dynamodb-connector
I a direct connection is needed we can use Simba Amazon DynamoDB ODBC and JDBC Drivers.

Category: Connectivity

Load More

Ontology Implementation

Connectivity

timbr supports both JDBC and ODBC. We reuse the thrift-server protocol of Apache Hive and Spark. This means you can connect to timbr’s Knowledge Graph using Hive/Spark JDBC/ODBC drivers (in most BI tools they already come embedded, so no installation needed).

Category: Connectivity

Creating an ontology: You can either use our Visual Ontology Modeler (no SQL needed) or use timbr extended SQL DDL statements.

Mapping data to the ontology: You can either use our Visual Ontology Data Mapper (no SQL needed) or use timbr’s extended SQL DDL statements.

Querying the Knowledge Graph: SQL, Python/R, dataframes, and natively in Apache Spark (SQL, Python, R, Java, Scala). GraphQL can be supported by integrating external open source projects that support the translation of GraphQL to SQL.

Category: Connectivity

Yes, GraphQL is supported by integrating external open source projects that support the translation of GraphQL to SQL.

Category: Connectivity

timbr supports query of JSON and XML using Apache Spark.

Category: Connectivity

Yes, this could be generated easily (creating the SQL DDL statements of timbr directly from the XML hierarchy/relationships).

Category: Connectivity

Yes, moving from SPARQL to timbr’s simplified SQL is quite trivial and easy to do.

Category: Connectivity

Yes, timbr works extensively with SQLAlchemy. Another valid option for python users is DataFrames.

Category: Connectivity

Yes, timbr is compatible with OWL-DL and some OWL-2 inferences.
If there is a clear business value to add more OWL-2 inferences, we can support them as well. timbr’s inference engine is based on query-rewriting techniques. If timbr encounters slow queries/performance, timbr can specifically materialize the part of knowledge that is required.

Category: Connectivity

yes.

Category: Connectivity

This is supported as part of our integration with Apache Spark/Apache Hive: https://github.com/awslabs/emr-dynamodb-connector
I a direct connection is needed we can use Simba Amazon DynamoDB ODBC and JDBC Drivers.

Category: Connectivity

Load More

Performance

Connectivity

timbr supports both JDBC and ODBC. We reuse the thrift-server protocol of Apache Hive and Spark. This means you can connect to timbr’s Knowledge Graph using Hive/Spark JDBC/ODBC drivers (in most BI tools they already come embedded, so no installation needed).

Category: Connectivity

Creating an ontology: You can either use our Visual Ontology Modeler (no SQL needed) or use timbr extended SQL DDL statements.

Mapping data to the ontology: You can either use our Visual Ontology Data Mapper (no SQL needed) or use timbr’s extended SQL DDL statements.

Querying the Knowledge Graph: SQL, Python/R, dataframes, and natively in Apache Spark (SQL, Python, R, Java, Scala). GraphQL can be supported by integrating external open source projects that support the translation of GraphQL to SQL.

Category: Connectivity

Yes, GraphQL is supported by integrating external open source projects that support the translation of GraphQL to SQL.

Category: Connectivity

timbr supports query of JSON and XML using Apache Spark.

Category: Connectivity

Yes, this could be generated easily (creating the SQL DDL statements of timbr directly from the XML hierarchy/relationships).

Category: Connectivity

Yes, moving from SPARQL to timbr’s simplified SQL is quite trivial and easy to do.

Category: Connectivity

Yes, timbr works extensively with SQLAlchemy. Another valid option for python users is DataFrames.

Category: Connectivity

Yes, timbr is compatible with OWL-DL and some OWL-2 inferences.
If there is a clear business value to add more OWL-2 inferences, we can support them as well. timbr’s inference engine is based on query-rewriting techniques. If timbr encounters slow queries/performance, timbr can specifically materialize the part of knowledge that is required.

Category: Connectivity

yes.

Category: Connectivity

This is supported as part of our integration with Apache Spark/Apache Hive: https://github.com/awslabs/emr-dynamodb-connector
I a direct connection is needed we can use Simba Amazon DynamoDB ODBC and JDBC Drivers.

Category: Connectivity

Load More

Connectivity

timbr supports both JDBC and ODBC. We reuse the thrift-server protocol of Apache Hive and Spark. This means you can connect to timbr’s Knowledge Graph using Hive/Spark JDBC/ODBC drivers (in most BI tools they already come embedded, so no installation needed).

Category: Connectivity

Creating an ontology: You can either use our Visual Ontology Modeler (no SQL needed) or use timbr extended SQL DDL statements.

Mapping data to the ontology: You can either use our Visual Ontology Data Mapper (no SQL needed) or use timbr’s extended SQL DDL statements.

Querying the Knowledge Graph: SQL, Python/R, dataframes, and natively in Apache Spark (SQL, Python, R, Java, Scala). GraphQL can be supported by integrating external open source projects that support the translation of GraphQL to SQL.

Category: Connectivity

Yes, GraphQL is supported by integrating external open source projects that support the translation of GraphQL to SQL.

Category: Connectivity

timbr supports query of JSON and XML using Apache Spark.

Category: Connectivity

Yes, this could be generated easily (creating the SQL DDL statements of timbr directly from the XML hierarchy/relationships).

Category: Connectivity

Yes, moving from SPARQL to timbr’s simplified SQL is quite trivial and easy to do.

Category: Connectivity

Yes, timbr works extensively with SQLAlchemy. Another valid option for python users is DataFrames.

Category: Connectivity

Yes, timbr is compatible with OWL-DL and some OWL-2 inferences.
If there is a clear business value to add more OWL-2 inferences, we can support them as well. timbr’s inference engine is based on query-rewriting techniques. If timbr encounters slow queries/performance, timbr can specifically materialize the part of knowledge that is required.

Category: Connectivity

yes.

Category: Connectivity

This is supported as part of our integration with Apache Spark/Apache Hive: https://github.com/awslabs/emr-dynamodb-connector
I a direct connection is needed we can use Simba Amazon DynamoDB ODBC and JDBC Drivers.

Category: Connectivity

Load More