Federated Queries Libraries

Prompt: which libraries exist to federate queries over multiple backends such as sql sparql graphql and the like?

ChatGPT:

Federating queries across multiple backend systems such as SQL, SPARQL, GraphQL, and others can be complex, but several libraries and frameworks are designed to handle this. These tools allow you to query multiple data sources with different query languages in a unified manner. Here are some of the key libraries and frameworks available: 1. Apache Drill

   Description: Apache Drill is an open-source SQL query engine that supports querying data from various sources including NoSQL databases, cloud storage, HDFS, and more. Drill allows you to query multiple data sources using standard SQL.
   Supported Backends: SQL databases, Hadoop, NoSQL (MongoDB, HBase), cloud storage (S3, Azure Blob), etc.
   Website: Apache Drill

2. Druid

   Description: Apache Druid is a real-time analytics database designed for fast slice-and-dice analytics on large datasets. Druid can query data across various sources, although it primarily focuses on time-series and log data.
   Supported Backends: SQL databases, real-time streams (Kafka), batch data (HDFS, S3), etc.
   Website: Apache Druid

3. Presto (Trino)

   Description: Presto (now known as Trino) is a distributed SQL query engine that can query data across multiple data sources. It's designed for interactive analytic queries and supports federating queries across different backends.
   Supported Backends: SQL databases, HDFS, S3, Kafka, NoSQL (Cassandra, MongoDB), and custom connectors.
   Website: Trino

4. GraphQL Mesh

   Description: GraphQL Mesh allows you to create a single GraphQL API that integrates multiple sources, including REST APIs, GraphQL, SQL databases, gRPC, and others. It can unify these different sources into a single GraphQL endpoint.
   Supported Backends: REST, GraphQL, SQL, OpenAPI, gRPC, SOAP, etc.
   Website: GraphQL Mesh

5. Hasura

   Description: Hasura is an open-source engine that gives you instant, real-time GraphQL APIs on your data, typically SQL databases, but it can also join data across multiple sources through remote schemas and REST endpoints.
   Supported Backends: SQL databases (PostgreSQL, MySQL), REST APIs, GraphQL.
   Website: Hasura

6. Federated SPARQL (Virtuoso, Apache Jena)

   Description: Federated SPARQL allows querying across multiple SPARQL endpoints or combining SPARQL with other data sources. Tools like Virtuoso and Apache Jena provide support for federated SPARQL queries.
   Supported Backends: SPARQL endpoints, relational databases (via wrappers), and other RDF stores.
   Websites: Virtuoso, Apache Jena

7. Linkurious Enterprise

   Description: Linkurious Enterprise is a tool that helps federate and visualize graph data across different sources, allowing queries across both SPARQL and other data sources.
   Supported Backends: SPARQL, SQL databases, graph databases (Neo4j, CosmosDB), etc.
   Website: Linkurious

8. Metaphactory

   Description: Metaphactory is a knowledge graph platform that supports federating queries across SPARQL endpoints and other types of data sources, offering a unified view for querying and visualizing data.
   Supported Backends: SPARQL, relational databases, and other data sources.
   Website: Metaphactory

9. Cayley

   Description: Cayley is a graph database that supports federating queries over different backends like SQL and NoSQL databases, providing a graph query language similar to Gremlin or GraphQL.
   Supported Backends: SQL, NoSQL, and custom backends.
   Website: Cayley

10. Stardog

   Description: Stardog is an enterprise data platform that unifies and federates data across various sources, allowing you to query across relational databases, graph databases, and other data silos using a combination of SPARQL, SQL, and GraphQL.
   Supported Backends: SPARQL, SQL, GraphQL, and others.
   Website: Stardog

These tools and libraries provide various capabilities to federate queries across multiple backends, depending on your specific needs and the types of data sources you are working with.

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