What's the difference between Flume and Sqoop?

Question

Both Flume and Sqoop are meant for data movement, then what is the difference between them? Under what condition should I use Flume or Sqoop?

Answer 1

Flume: A very common use case is collecting log data from one system- a bank of web servers(aggregating it in HDFS for later analysis).

Sqoop: On the other hand is designed for performing bulk imports of data into HDFS from structured data stores. simple use case will be an organization that runs a nightly sqoop import to load the day's data from a production DB into a Hive data ware house for analysis.

--From the definitive guide.

Answer 2

1. Apache Sqoop and Apache Flume work with various kinds of data sources. Flume functions well in streaming data sources which are generated continuously in hadoop environment such as log files from multiple servers.

whereas Apache Sqoop is designed to work well with any kind of relational database system that has JDBC connectivity.

2. Sqoop can also import data from NoSQL databases like MongoDB or Cassandra and also allows direct data transfer or Hive or HDFS. For transferring data to Hive using Apache Sqoop tool, a table has to be created for which the schema is taken from the database itself.

3. In Apache Flume data loading is event driven whereas in Apache Sqoop data load is not driven by events.

4.Flume is a better choice when moving bulk streaming data from various sources like JMS or Spooling directory whereas Sqoop is an ideal fit if the data is sitting in databases like Teradata, Oracle, MySQL Server, Postgres or any other JDBC compatible database then it is best to use Apache Sqoop.

5.In Apache Flume, data flows to HDFS through multiple channels whereas in Apache Sqoop HDFS is the destination for importing data.

6.Apache Flume has agent based architecture i.e. the code written in flume is known as agent which is responsible for fetching data whereas in Apache Sqoop the architecture is based on connectors. The connectors in Sqoop know how to connect with the various data sources and fetch data accordingly.

Lastly, Sqoop and Flume cannot be used achieve the same tasks as they are developed specifically to serve different purposes. Apache Flume agents are designed to fetch streaming data like tweets from Twitter or log file from the web server whereas Sqoop connectors are designed to work only with structured data sources and fetch data from them.

Apache Sqoop is mainly used for parallel data transfers, for data imports as it copies data quickly where Apache Flume is used for collecting and aggregating data because of its distributed, reliable nature and highly available backup routes.

Answer 3

Sqoop and Flume both are meant to fulfill data ingestion needs but they serve different purposes. Apache Flume works well for streaming data sources that are generated continuously in hadoop environment such as log files from multiple servers whereas whereas Apache Sqoop works well with any RDBMS has JDBC connectivity.

Sqoop is actually meant for bulk data transfers between hadoop and any other structured data stores. Flume collects log data from many sources, aggregating it, and writing it to HDFS.

I came across this interesting infographic that explains the differences between the two apache projects Sqoop and Flume -

Difference between Sqoop and Flume

Answer 4

Sqoop

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• Sqoop can perform import/export from RDBMS to HDFS/HIVE/HBASE
• sqoop only import/export structured data not unstructured or semi structured.

Flume

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• import stream data from multiple sources mostly semi-structured and unstructured in nature. Now Kafka is better alternative for flume.

Answer 5

From http://flume.apache.org/

Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data.

Flume helps to collect data from a variety of sources, like logs, jms, Directory etc.
Multiple flume agents can be configured to collect high volume of data.
It scales horizontally.

From http://sqoop.apache.org/

Apache Sqoop(TM) is a tool designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.

Sqoop helps to move data between hadoop and other databases and it can transfer data in parallel for performance.

Answer 6

Flume:

  Flume is a framework for populating Hadoop with data. Agents are populated 
  throughout ones IT infrastructure – inside web servers, application servers
  and mobile devices, for example – to collect data and integrate it into Hadoop.

Sqoop:

  Sqoop is a connectivity tool for moving data from non-Hadoop data stores – such
  as relational databases and data warehouses – into Hadoop. It allows users to 
  specify the target location inside of Hadoop and instruct Sqoop to move data 
  from Oracle,Teradata or other relational databases to the target. 

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