Apache Gobblin
E705297
Apache Gobblin is an open-source distributed data integration framework designed for large-scale data ingestion, replication, and lifecycle management across diverse data sources and sinks.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Apache Gobblin canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T7985867 — 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.
Target entity: Apache Gobblin Context triple: [Apache Sqoop, supersededBy, Apache Gobblin]
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A.
Apache Oozie
Apache Oozie is a workflow scheduler system designed to manage and coordinate Hadoop jobs such as MapReduce, Pig, and Hive in complex data processing pipelines.
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B.
Apache Flink
Apache Flink is an open-source distributed stream-processing framework designed for high-throughput, low-latency data processing and real-time analytics on large-scale data.
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C.
Apache Flume
Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log and event data into Hadoop and other data stores.
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D.
Apache Beam
Apache Beam is an open-source unified programming model for defining and executing batch and streaming data processing pipelines across multiple execution engines.
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E.
Apache Storm
Apache Storm is a distributed real-time computation system designed for processing large streams of data with low latency and high fault tolerance.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: Apache Gobblin Target entity description: Apache Gobblin is an open-source distributed data integration framework designed for large-scale data ingestion, replication, and lifecycle management across diverse data sources and sinks.
-
A.
Apache Tez
Apache Tez is a distributed data processing framework designed for building high-performance batch and interactive data workflows on Hadoop.
-
B.
Apache Oozie
Apache Oozie is a workflow scheduler system designed to manage and coordinate Hadoop jobs such as MapReduce, Pig, and Hive in complex data processing pipelines.
-
C.
Apache Flink
Apache Flink is an open-source distributed stream-processing framework designed for high-throughput, low-latency data processing and real-time analytics on large-scale data.
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D.
Apache Flume
Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log and event data into Hadoop and other data stores.
-
E.
Apache Beam
Apache Beam is an open-source unified programming model for defining and executing batch and streaming data processing pipelines across multiple execution engines.
- F. None of above. chosen
Statements (53)
| Predicate | Object |
|---|---|
| instanceOf |
Apache Software Foundation project
ⓘ
distributed data ingestion framework ⓘ open-source data integration framework ⓘ |
| developer | Apache Software Foundation NERFINISHED ⓘ |
| donatedTo | Apache Software Foundation NERFINISHED ⓘ |
| feature |
checkpointing
ⓘ
config-driven job specification ⓘ fault tolerance ⓘ job scheduling ⓘ metrics collection ⓘ monitoring and alerting ⓘ pluggable source and sink architecture ⓘ schema management ⓘ task parallelism ⓘ watermarking ⓘ |
| license | Apache License 2.0 ⓘ |
| originatedAt | LinkedIn NERFINISHED ⓘ |
| programmingLanguage | Java ⓘ |
| repository | https://github.com/apache/gobblin ⓘ |
| supportsDataSourceType |
NoSQL databases
ⓘ
RDBMS ⓘ REST APIs ⓘ file systems ⓘ message queues ⓘ |
| supportsDeploymentModel |
MapReduce-based deployment
ⓘ
YARN-based deployment ⓘ cluster mode ⓘ containerized deployment ⓘ service mode ⓘ standalone mode ⓘ |
| supportsEnvironment |
cloud deployments
ⓘ
hybrid deployments ⓘ on-premises deployments ⓘ |
| supportsPlatform |
Apache Helix
NERFINISHED
ⓘ
Apache Kafka NERFINISHED ⓘ Apache YARN NERFINISHED ⓘ Hadoop NERFINISHED ⓘ Kubernetes NERFINISHED ⓘ |
| supportsSinkType |
HDFS
NERFINISHED
ⓘ
Kafka NERFINISHED ⓘ RDBMS ⓘ data warehouses ⓘ object stores ⓘ |
| supportsUseCase |
ETL
ⓘ
data compaction ⓘ data integration ⓘ data lifecycle management ⓘ data migration ⓘ data quality management ⓘ data replication ⓘ large-scale data ingestion ⓘ metadata management ⓘ |
| website | https://gobblin.apache.org/ ⓘ |
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.
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.
Subject: Apache Gobblin Description of subject: Apache Gobblin is an open-source distributed data integration framework designed for large-scale data ingestion, replication, and lifecycle management across diverse data sources and sinks.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.