Name: Apache Sqoop
Rating: 8.8 (4 reviews)
Author: Apache

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### Data Integration
Users generally praise Apache Sqoop for its efficient data integration capabilities. The tool is commended for its ease of use in transferring data between relational databases and Hadoop, making the process simple and straightforward. Users appreciate Sqoop's ability to handle bulk and delta data transfers effectively, especially in scenarios where data needs to be moved between different environments. Despite some minor issues with connectors and data formats, Sqoop remains a reliable choice for organizations looking to streamline their data integration processes.

### Data Migration
Reviewers consistently highlight Apache Sqoop's efficiency in migrating data between RDBMS and Hadoop environments. Users appreciate the ease of configuring real-time data transfers from source systems and the ability to perform incremental imports and exports. However, some users find the process of re-importing data whenever changes occur to be a drawback. Despite some concerns about performance and data policy compliance, Apache Sqoop remains a popular choice for data migration projects, especially in scenarios where leveraging Transact SQL integration is essential.

### Database Management
Some users praise Apache Sqoop for its ability to efficiently transfer structured data between RDBMS and Hadoop clusters. They find it convenient and effective, especially when integrated with other tools for data transformation. However, there are concerns about Sqoop's limitations, particularly its focus on structured data and the lack of support for unstructured data. Users also highlight the importance of using the correct connectors, drivers, and connection managers to ensure successful data transfers. Despite these challenges, Apache Sqoop remains a popular choice for migrating data between RDBMS systems and Hadoop environments.

### Data Transfer Techniques
Users generally find Apache Sqoop's data transfer capabilities to be a standout feature in their reviews. The tool's command line interface is praised for its simplicity and efficiency in transferring data between RDBMS and Hadoop. While some users appreciate the lightweight commands and the ease of importing data, others highlight the speed of execution when loading data from PostgreSQL to HDFS. However, there are minor issues reported, such as the need for correct connectors, drivers, and connection manager names, as well as potential challenges with data formats in HDFS or Hive tables. Despite these challenges, users acknowledge Sqoop's incremental load and job features as valuable assets for data transfer tasks.

### Hadoop Ecosystem Tools
Users have varied opinions on Apache Sqoop's capabilities within the Hadoop ecosystem tools, particularly in relation to map reduce, Hive, and distributed file systems. While some users praise Sqoop for its simplicity and effectiveness in importing data from external datastores into Hadoop Distributed File System, others express concerns about the lack of a graphical user interface and the perceived slowness of MapReduce functions. Despite these mixed reviews, it is evident that Sqoop plays a significant role in facilitating data integration within the Hadoop ecosystem.

Users have made several recommendations for Apache Sqoop based on their experiences with the tool. Firstly, they suggest contacting customer support before purchasing Apache Sqoop to address any concerns and ensure it meets specific requirements. Secondly, users highly recommend Apache Sqoop for data transfer between relational databases and Hadoop. They find it easy to use and efficient, especially for importing SQL databases into Hadoop data lakes. Additionally, users appreciate its ability to handle bulk and delta data transfers from RDBMS to Hadoop environments. Lastly, users recommend Apache Sqoop for its integration capabilities with other tools in the Hadoop ecosystem. They find it useful for transforming data batches and consider it one of the best ETL (Extract, Transform, Load) tools they have used. Some users also suggest adding file import functionality to enhance its capabilities further. Overall, users suggest giving Apache Sqoop a try as it is considered a highly recommended tool for data transfer between relational databases and Hadoop.

Apache Sqoop is a tool for use with Hadoop, used to transfer data between Apache Hadoop and other, structured data stores.

Cloudera Manager is a management application for Apache Hadoop and the enterprise data hub, from Cloudera. Its automated wizards let users quickly deploy a cluster, no matter what the scale or the deployment environment, complete with intelligent, system-based default settings.

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Apache Sqoop

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Likelihood to Recommend

The Apache Software Foundation provides support for the Apache community of open-source software projects. The Apache projects are characterized by a collaborative, consensus based development process, an open and pragmatic software license, and a desire to create high quality software that leads the way in its field.

We consider ourselves not simply a group of projects sharing a server, but rather a community of developers and users.

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Apache Sqoop 2018-02-17 14:43:29

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Multiple tables

Time consuming

Supports multiple

External data

Data sources

Import and export

External data sources

Export features

Parallel processing

Export import

Quick and efficient

Import data

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Hadoop-Related Software

Sqoop is being used to offload relational databases into Hadoop HDFS, Hive, or HBase. From there, big data analysis processes can be run, then Sqoop is used to reload different tables in the source database for relational queries by external systems such as web applications. 

Sqoop helps bridge the gap between traditional RDBMS systems and the Hadoop ecosystem.

Provides generalized JDBC extensions to migrate data between most database systems
Generates Java classes upon reading database records for use in other code utilizing Hadoop's client libraries
Allows for both import and export features

Sqoop2 development seems to have stalled. I have set it up outside of a Cloudera CDH installation, and I actually prefer it's "Sqoop Server" model better than just the CLI client version that is Sqoop1. This works especially well in a microservices environment, where there would be only one place to maintain the JDBC drivers to use for Sqoop.

When combined with Cloudera's HUE, it can enable non-technical users to easily import relational data into Hadoop.
Being able to manipulate large datasets in Hadoop, and them load them into a type of "materialized view" in an external database system has yielded great insights into the Hadoop datalake without continuously running large batch jobs.
Sqoop isn't very user-friendly for those uncomfortable with a CLI.

Apache Kafka, Apache Flume, Apache Spark, Apache Pig, Qubole, Amazon Elastic MapReduce, Cloudera Manager, Amazon Relational Database Service, Amazon S3 (Simple Storage Service), Logstash, Elasticsearch, Splunk Enterprise

Apache Sqoop

Overview

What is Apache Sqoop?