Presto vs Impala

Updated April 4, 2023

Difference Between Presto vs Impala

Impala and Presto (or Presto DB) are a distributed SQL query engine and a native analytic database designed from the ground up for fast analytic queries on any size of data meanwhile Both works well for BI Queries and are open Source OLAP engines respectively. The fact that Amazon Web Services and MapR have both acquired support for Impala in less than two years demonstrates its rapid ascent. Presto took over the Hive in 2012 and was faster than other engines around 20x. Presto is not a database but we could store data and is built on java to deliver ad-hoc analytic.

Head to Head Comparison Between Presto vs Impala (Infographics)

Below are the top differences between Presto and Impala:

Key Differences

Next, we shall see a few key differences between Presto and Impala.

1. Apache Impala is a modern Real-time Query for HDFS and Presto is an Open-source Distributed SQL Engine and both belong to Big Data Tools.
2. Impala is written in C++ and java and presto is built in java.
3. The Unique Key factor of Presto was it works directly on Files with no ETL formats and Impala is considered to be a super-fast performer. Though it is considered faster presto is much more Pluggable. Impala has efficient metadata caching.
4. Impala Supports HDFS for storage whereas Presto lacks it. Presto directly communicates with HDFS and has connectors with them to have communicated with data sources. Presto doesn’t have data limitations as we generate hourly or daily reports, for example, Facebook users.
5. Presto concept was developed from a parallel database named Volcano and designed for high-speed data analysis. But Impala is designed for PB level real-time query analysis for the CDH platform. Impala is a good option for reducing query latency, especially for concurrent executions. Presto is used for an increased workload.
6. Presto was created to make query processing in commercial data warehouses faster. It has the potential to scale the organizational size to match Facebook.
7. Impala doesn’t use Hive and MapReduce but prefers relational databases. As Presto is memory-based it is found that it takes less memory when Querying compared to Impala.
8. Impala is connected with Hadoop’s inherent security and Kerberos for authentication. Data Access is controlled here.LDAP authentication is done in Presto.
9. The ORC, Parquet, and RCFile file formats are all supported by Presto. As a result, it’s regarded as a fantastic query engine that also eliminates the requirement for data transformation.  RCFile, Parquet, Avro file, and Sequence File formats are supported by Impala.
10. Presto stores intermediate results in a Buffer cache and Impala doesn’t use MapReduce to store an intermediate result instead uses In-Memory and hence gives slow processing.

Comparison Table

At all times, developers are on the search for practical and efficient SQL engines. The Impala and Presto engines have been the most popular among those available on the market. Let’s see a head-to-head comparison of Presto and Impala to see their insights and practices.

Presto installation is given here:

$ tar  -zxf  presto-server-0.149.tar.gz
$ cd presto-server-0.149

Presto Server Configuration

$ cd etc
$ vi config.properties
coordinator = true
node-scheduler.include-coordinator = true
http-server.http.port = 8080
query.max-memory = 5GB
query.max-memory-per-node = 1GB
discovery-server.enabled = true
discovery.uri = http://localhost:8080

Sample application in Presto

public class Prestodemo {
public static void main(String[] args) {
Connection connection = null;
Statement sta = null;
try {
Class.forName("com.facebook.presto.jdbc.PrestoDriver");
connection = DriverManager.getConnection(
"jdbc:presto://localhost:8080/mysql/demo", "test", “");
sta= connection.createStatement();
String sql;
sql = "select auth_id, auth_name from mysql.tutorials.author”;
}
}

Conclusion

Choosing the right database or SQL engine is entirely dependent on your needs. We’ve highlighted some of the most widely used and beneficial aspects of all SQL engines in this article. Through the specific features and properties, we listed in the comparison give easier choice for the user. We have the option of using Presto or Impala. The repository of choice is determined by technological specs and feature availability.

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