This post covers a brief comparison between the Data Ingestion Tools: Apache Sqoop vs Apache Flume in BigData Hadoop.
We got to know that some of our trainees are getting Confused about Apache Sqoop vs Apache Flume, so, we thought of writing this blog and if you go through till the end of this post, you will find all your doubts cleared.
If you are just starting out in BigData & Hadoop then I highly recommend you to go through these posts below, first:
- Big Data Hadoop Keypoints & Things you must know to Start learning Big Data & Hadoop, check here
- Big Data & Hadoop Overview, Concepts, Architecture, including Hadoop Distributed File System (HDFS), Check here
- Hadoop Distribution: Cloudera vs Hortonworks, to know which one is better, check here
Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using Hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment.
Data ingestion is important in any big data project because the volume of data is generally in petabytes or exabytes. Hadoop Sqoop and Hadoop Flume are the two tools in Hadoop which is used to gather data from different sources and load them into HDFS. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., and Flume in Hadoop is used to sources data which is stored in various sources like and deals mostly with unstructured data.
Apache Sqoop and Apache Flume are two popular open source tools for Hadoop that help organizations overcome the challenges encountered in data ingestion.
While working on Hadoop, there is always one question occurs that if both Sqoop and Flume are used to gather data from different sources and load them into HDFS so why we are using both of them.
So, in this post, BigData Hadoop: Apache Sqoop vs Apache Flume we will answer this question. At first, we will understand the brief introduction of both tools. Afterward, we will learn comparison of Apache Flume vs Sqoop to understand each tool.
What is Apache Sqoop?
Apache Sqoop is a lifesaver in moving data from the data warehouse into the Hadoop environment. Interestingly it named Sqoop as SQL-to-Hadoop. Basically, for importing data from RDBMS’s like MySQL, Oracle, etc. into HBase, Hive or HDFS Apache Sqoop is an effective Hadoop tool.
What is Apache Flume?
Basically, for streaming logs into Hadoop environment, Apache Flume is best service designed. Also for collecting and aggregating huge amounts of log data, Flume is a distributed and reliable service.
Difference Between Apache Sqoop vs Flume
As you have already learned above Sqoop and Flume, both are primarily two Data Ingestion tools used in the Big Data world, now still 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.
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