Sqoop vs Flume – Feature Wise Comparison
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1. Objective – Sqoop vs Flume
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 article, Apache Sqoop vs 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 in detail.
So, let’s start the comparison of Sqoop vs Flume.
2. Introduction to Apache Sqoop and Flume
a. What is Apache Sqoop?
For anyone who is experiencing difficulties, 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. Also, we can export data from HDFS into RDBMS through Sqoop. In addition, Sqoop is a command line interpreter. Since interpreter executes Sqoop commands one at a time.
To know more about Sqoop, follow these links Sqoop Features & Sqoop Architecture
b. 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. Moreover, it has very simple and easy to use architecture, on the basis of streaming data flows. Also, it has tunable reliability mechanisms and several recoveries and failover mechanisms.
Click here to install Apache Flume
3. Sqoop vs Flume – Feature Wise Difference
a. Data Flow
Sqoop works with any type of relational database system (RDBMS) that has the basic JDBC connectivity. Also, Sqoop can import data from NoSQL databases like MongoDB, Cassandra and along with it. Moreover, it allows data transfer to Apache Hive or HDFS.
Flume works with streaming data sources those are generated continuously in Hadoop environments. Like log files.
b. Type of Loading
The Sqoop load is not driven by events.
Here, data loading is completely event-driven.
c. When to use
However, if the data is being available in Teradata, Oracle, MySQL, PostreSQL or any other JDBC compatible database it is considered an ideal fit.
While we move bulk of streaming data from sources likes JMS or spooling directories, it is the best choice.
d. Link to HDFS
It has connector based architecture. That means the connectors know a great deal in connecting with the various data sources. Also to fetch data correspondingly.
It has agent-based architecture. That means code written in Flume is we call agent that may responsible for fetching the data.
f. Fetch Data
Specifically to work with structured data sources and to fetch data from them alone we use Apache Sqoop connectors.
Specifically to fetch streaming data like tweets from Twitter or log files from Web servers or application servers etc we use Apache Flume.
g. Where to use
Basically, we use Apache Sqoop for parallel data transfers, data imports as it copies the data pretty quick.
Basically, we use Apache Flume for collecting and aggregating data because of its distributed, reliable nature. Also due to its highly available backup routes.
- Sqoop can import the complete database or individual tables into HDFS, so we can say it supports bulk import.
- For optimal system utilization and fast performance, Sqoop parallelizes data transfer.
- It can map relational databases and import directly into HBase and Hive, so we can say it offers direct input.
- Also, makes data analysis efficient.
- Sqoop helps in mitigating the excessive loads to external systems.
- By generating Java classes it offers data interaction programmatically.
- Flume allows to scale in environments with as low as five machines to as high as several thousands of machines. Hence, it is considered as a flexible tool.
- Apache Flume offers high throughput and low latency.
- Also, offers ease of extensibility even though it has a declarative configuration.
- Flume is fault-tolerant, linearly scalable and stream oriented.
i. Usage in Companies
- A great company, “The Apollo Group education company” uses Sqoop. They use it to extract data from external databases and inject results of Hadoop jobs back into the RDBMS’s.
- Moreover, the company like Coupons.com uses Sqoop tool. They use it for data transfer between its IBM Netezza data warehouse and the Hadoop environment.
- To transfer logs from the production systems into HDFS the company “Goibibo” uses Hadoop flume.
- Also, the company like “Mozilla” uses flume for the BuildBot project along with Elastic Search.
- The company like “Capillary technologies” also uses Flume for aggregating logs from 25 machines in production.
So, this was all in Sqoop vs Flume tutorial. Hope you like our explanation.
4. Conclusion – Sqoop vs Flume
So, we have seen all the differences between Apache Sqoop vs Flume. Still, if you feel to ask any query. Feel free to ask in the comment section.
See also- Apache Flume Installation & Best Sqoop Books