Apache Sqoop
E185679
Apache Sqoop is an open-source tool designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Apache Sqoop canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T1647858 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Apache Sqoop Context triple: [Hadoop, ecosystemIncludes, Apache Sqoop]
-
A.
Hadoop
Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets across clusters of commodity hardware.
-
B.
Google Cloud Dataproc
Google Cloud Dataproc is a managed cloud service for running Apache Hadoop, Spark, and other big data workloads on scalable, automated clusters in Google Cloud.
-
C.
Amazon Redshift
Amazon Redshift is a fully managed, cloud-based data warehousing service from Amazon Web Services designed for fast querying and analysis of large datasets using SQL.
-
D.
AWS Glue
AWS Glue is a fully managed extract, transform, and load (ETL) service from Amazon Web Services that simplifies data preparation and integration for analytics and data warehousing.
-
E.
Oracle Data Integrator
Oracle Data Integrator is an Oracle ETL and data integration platform designed for high-performance data movement, transformation, and synchronization across heterogeneous systems.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Apache Sqoop Target entity description: Apache Sqoop is an open-source tool designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.
-
A.
Hadoop
Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets across clusters of commodity hardware.
-
B.
Google Cloud Dataproc
Google Cloud Dataproc is a managed cloud service for running Apache Hadoop, Spark, and other big data workloads on scalable, automated clusters in Google Cloud.
-
C.
Amazon Redshift
Amazon Redshift is a fully managed, cloud-based data warehousing service from Amazon Web Services designed for fast querying and analysis of large datasets using SQL.
-
D.
AWS Glue
AWS Glue is a fully managed extract, transform, and load (ETL) service from Amazon Web Services that simplifies data preparation and integration for analytics and data warehousing.
-
E.
Oracle Data Integrator
Oracle Data Integrator is an Oracle ETL and data integration platform designed for high-performance data movement, transformation, and synchronization across heterogeneous systems.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
Apache Software Foundation project
ⓘ
data transfer tool ⓘ open-source software ⓘ software tool ⓘ |
| category |
Big data
ⓘ
Data management software ⓘ |
| developer | Apache Software Foundation ⓘ |
| feature |
Kerberos authentication support
ⓘ
code generation for Java classes ⓘ command-line interface ⓘ direct mode for some databases ⓘ incremental data import ⓘ integration with MapReduce ⓘ parallel data transfer ⓘ support for compression during transfer ⓘ support for delimiters and field mapping ⓘ |
| genre |
ETL tool
ⓘ
data integration ⓘ |
| initialReleaseYear | 2009 ⓘ |
| license | Apache License 2.0 ⓘ |
| nameOrigin | portmanteau of SQL and Hadoop ⓘ |
| operatingSystem | cross-platform ⓘ |
| partOf | Apache Hadoop ecosystem ⓘ |
| programmingLanguage | Java ⓘ |
| purpose |
bulk data transfer between Hadoop and relational databases
ⓘ
export data from Hadoop to relational databases ⓘ import data from relational databases into Hadoop ⓘ |
| reasonForRetirement | lack of active community ⓘ |
| repository | https://github.com/apache/sqoop ⓘ |
| retiredBy | Apache Software Foundation ⓘ |
| retirementDate | 2021-06-16 ⓘ |
| status | retired ⓘ |
| supersededBy |
Apache Gobblin
ⓘ
Apache NiFi ⓘ Apache Spark-based ingestion solutions ⓘ |
| supportsDataStoreType |
relational database
ⓘ
structured datastore ⓘ |
| supportsPlatform |
Hadoop
ⓘ
surface form:
Apache Hadoop
|
| supportsSource |
IBM DB2
ⓘ
surface form:
DB2
SQL Server ⓘ
surface form:
Microsoft SQL Server
MySQL ⓘ Oracle Database ⓘ PostgreSQL ⓘ |
| supportsTarget |
Apache HBase
ⓘ
surface form:
HBase
HDFS ⓘ Apache Hive ⓘ
surface form:
Hive
|
| uses | JDBC ⓘ |
| website | https://sqoop.apache.org/ ⓘ |
| writtenIn | Java ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Apache Sqoop Description of subject: Apache Sqoop is an open-source tool designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.