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Posted to dev@gobblin.apache.org by GitBox <gi...@apache.org> on 2021/01/26 17:53:00 UTC

[GitHub] [incubator-gobblin] sv2000 commented on a change in pull request #3212: [GOBBLIN-1371] Improve README to reflect current capabilities

sv2000 commented on a change in pull request #3212:
URL: https://github.com/apache/incubator-gobblin/pull/3212#discussion_r564710086



##########
File path: README.md
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@@ -6,11 +6,32 @@
 [![Join us on Slack](https://img.shields.io/badge/slack-apache--gobblin-brightgreen.svg)](https://communityinviter.com/apps/apache-gobblin/apache-gobblin)
 [![codecov.io](https://codecov.io/github/apache/incubator-gobblin/branch/master/graph/badge.svg)](https://codecov.io/github/apache/incubator-gobblin)
 
-Apache Gobblin is a universal data ingestion framework for extracting, transforming, and loading large volume of data from a variety of data sources: databases, rest APIs, FTP/SFTP servers, filers, etc., onto Hadoop. 
+Apache Gobblin is a highly scalable data management solution for structured and byte-oriented data in heterogeneous data ecosystems. 
 
-Apache Gobblin handles the common routine tasks required for all data ingestion ETLs, including job/task scheduling, task partitioning, error handling, state management, data quality checking, data publishing, etc. 
+It offers the following capabilities:
+- Ingestion and export of data from a variety of sources and sinks into and out of the data lake. Gobblin is optimized and designed for ELT patterns with inline transformations on ingest (small t).

Review comment:
       Do you think we can move this sentence to the top para after "Apace Gobblin is a highly scalable..."?

##########
File path: README.md
##########
@@ -6,11 +6,32 @@
 [![Join us on Slack](https://img.shields.io/badge/slack-apache--gobblin-brightgreen.svg)](https://communityinviter.com/apps/apache-gobblin/apache-gobblin)
 [![codecov.io](https://codecov.io/github/apache/incubator-gobblin/branch/master/graph/badge.svg)](https://codecov.io/github/apache/incubator-gobblin)
 
-Apache Gobblin is a universal data ingestion framework for extracting, transforming, and loading large volume of data from a variety of data sources: databases, rest APIs, FTP/SFTP servers, filers, etc., onto Hadoop. 
+Apache Gobblin is a highly scalable data management solution for structured and byte-oriented data in heterogeneous data ecosystems. 
 
-Apache Gobblin handles the common routine tasks required for all data ingestion ETLs, including job/task scheduling, task partitioning, error handling, state management, data quality checking, data publishing, etc. 
+It offers the following capabilities:
+- Ingestion and export of data from a variety of sources and sinks into and out of the data lake. Gobblin is optimized and designed for ELT patterns with inline transformations on ingest (small t).
+- Data Organization within the lake (e.g. compaction, partitioning, deduplication)
+- Lifecycle Management of data within the lake (e.g. data retention)
+- Compliance Management of data across the ecosystem (e.g. fine-grain data deletions)
+
+Common Patterns used in production
+- Stream / Batch ingestion of Kafka to Data Lake (HDFS, S3, ADLS)
+- Bulk-loading serving stores from the Data Lake (e.g. HDFS -> Couchbase)
+- Support for data sync across Federated Data Lake (HDFS <-> HDFS, HDFS <-> S3, S3 <-> ADLS)
+- Integrate external vendor API-s (e.g. Salesforce, Dynamics etc.) with data store (HDFS, Couchbase etc)
+- Enforcing Data retention policies and GDPR deletion on HDFS / ADLS
+
+Highlights
+- Battle tested at scale: Runs in production at petabyte-scale at companies like LinkedIn, PayPal, Verizon etc.
+- Feature rich: Supports job/task scheduling, task partitioning, fault tolerance, error handling, state management for incremental processing, data quality checking, atomic data publishing etc.
+- Supports stream and batch execution modes 
+- Control Plane (Gobblin-as-a-service) supports programmatic triggering and orchestration of data plane operations. 
+
+Apache Gobblin is NOT
+- A general purpose data transformation engine like Spark or Flink. Gobblin can delegate complex-data processing tasks to Spark, Hive etc. 
+- A data storage system like Apache Kafka or HDFS. Gobblin integrates with these systems as sources or sinks. 
+- A general-purpose workflow execution system like Airflow, Azkaban, Dagster, Luigi. You can use these systems to kick-off Gobblin jobs or use Gobblin’s in-built Quartz based scheduler. 

Review comment:
       We can mention here that Gobblin-as-a-Service has a workflow execution system for scheduling and orchestrating Gobblin jobs.




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