Differences Between to Sqoop and Flume
Big Data applies to information that cannot be processed or analyzed using traditional (RDBMS) process or tools. So large amount of data is required for analytical processing and this data is loaded from different sources into Hadoop clusters (i.e. a cluster used for storing and analyzing a huge amount of data in a distributed manner). Sourcing of this bulk data into Hadoop clusters from different sources faces a problem like maintaining and ensuring data consistency since each data source could have data in varied form and structure. The best way of collecting, aggregating, and moving large amounts of data between the Hadoop Distributed File System and RDBMS is via using tools such as Sqoop or Flume.
Let’s discuss these two commonly used tools for the above-mentioned purpose.
What is Sqoop
Sqoop is an open source software product from Apache Software.With Sqoop, you can import data from an RDBMS or mainframe into HDFS. To use Sqoop, a user has to specify the tool user want to use and the arguments that control the particular tool. You can also then export the data back into an RDBMS using Sqoop. The export functionality of Sqoop is used to extract useful information from Hadoop and export them to the outside structured data stores. It works with different databases like Teradata, MySQL, Oracle, HSQLDB.
- Sqoop Architecture: –
Architecture of Sqoop
The connector in a Sqoop is a plugin for a particular Database source, so it is fundamental that it is a piece of Sqoop establishment. Despite the fact that drivers are database-specific pieces and distributed by various database vendors, Sqoop itself comes bundled with different types of connectors utilized for prevalent database and information warehousing system. Thus Sqoop ships with a mixed variety of connectors out of the box as well. Sqoop gives a pluggable component for ideal network and external system. The Sqoop API gives a helpful structure for assembling new connectors and therefore any database connectors can be dropped into Sqoop installation to give connectivity to different data systems.
What is Flume
Flume is also from Apache software and is capable of collecting and moving the recursively generating data i.e., logs, crash report etc. The Apache Flume is not only restricted to log data aggregation but data sources are customizable and thus Flume can be used to transport massive quantities of data including but not limited to email messages, social-media-generated data, network traffic data and pretty much any data source possible.
Flume architecture: –Flume architecture is based on many core concepts:
- Flume Event- it is represented as the unit of data flowing, which has a byte payload and set of strings with optional string headers. Flume considers an event just a generic blob of bytes.
- Flume Agent- It is a JVM process that hosts the components such as channels, sink, and sources. It has a potential to receive, store and forward the events from an external source to the next level.
- Flume Flow- it is the point of time the event is being generated.
- Flume Client- it refers to the interface where the client operates at the origin point of the event and delivers it to the Flume agent.
- Source- A source is one that consumes events having a specific format and delivers it via a specific mechanism.
- Channel- It is a passive store where events are held by until the sink removes it for further transport.
- Sink – It removes the event from a channel and put it on an external repository like HDFS. It currently supports creating text and sequence files and supports compression in both file types.
Architecture of Flume
Head to Head Comparison between Sqoop vs Flume (Infographics)
Below is the top 7 comparison between Sqoop vs Flume
Key Differences between Sqoop vs Flume
We now know that there are many differences between Sqoop vs Flume, here are the most important differences between them given below –
1. Sqoop is designed to exchange mass information between Hadoop and Relational Database.
Whereas, Flume is used to collect data from different sources which are generating data regarding a particular use case and then transferring this large amount of data from distributed resources to a single centralized repository.
2. Sqoop also includes set of commands which allows you to inspect the database you are working with. Thus we can consider Sqoop as a collection of related tools.
While collecting the date Flume scales the data horizontally and multiple Flume agents can be put in action to collect the date and aggregate them. Thereafter data logs are moved to a centralized data store i.e. Hadoop Distributed File System (HDFS).
3.The key factor for using Flume is that the data must be generated in a continuous and streaming fashion. Similarly, Sqoop is the best suited in situations when your data lives in database systems such as MySQL, Oracle, Teradata, PostgreSQL
Sqoop vs Flume (Comparison Table)
|Basis for Comparison||SQOOP||FLUME|
|Sqoop works well with any RDBMS which has JDBC (Java Database Connectivity) like Oracle, MySQL, Teradata, etc.||Flume works well for Streaming data source which is continuously generating such as logs, jms, directory, crash reports, etc.|
|Data Flow||Sqoop specifically used for parallel data transfer. For this reason, the output could be in multiple files||Flume is used for collecting and aggregating data because of its distributed nature.|
|Sqoop is not driven by events.||Flume is completely event-driven.|
|Sqoop follows connector-based architecture, which means connectors, knows how to connect to a different data source.||Flume follows agent-based architecture, where the code written in it is known as an agent which is responsible for fetching data.|
|Where to use||Primarily used for copying data faster and then using it for generating analytical outcomes.||Generally used to pull data when companies want to analyze patterns, root causes or sentiment analysis using logs and social media.|
|Performance||It reduces the excessive storage and processing loads by transferring them to other system and has fast performance.||Flume is fault tolerant, robust and has tenable reliability mechanism for failover and recovery.
|Release History||First version of Apache Sqoop was launched in March 2012. The current stable release is 1.4.7||First stable version 1.2.0 of Apache Flume was launched in June 2012.The current stable release is Apache Flume Version 1.8.0.|
Conclusion – Sqoop vs Flume
As you learned above Sqoop and Flume, both are primarily two Data Ingestion tools used is Big Data world. If you need to ingest textual log data into Hadoop/HDFS then Flume is the right choice for doing that. If your data is not regularly generated then Flume will still work but it will be an overkill for that situation. Similarly, Sqoop is not the best fit for event-driven data handling.
This has been a guide to differences between Sqoop vs Flume, their Meaning, Head to Head Comparison, Key Differences, Comparison Table, and Conclusion. this article consists of all useful difference between Sqoop and Flume. You may also look at the following articles to learn more