What is Impala?

Impala is an open-source software which comes under the category of Massive Parallel Processing SQL query engine. It helps to process huge volumes of data that is stored in the Hadoop cluster. It was developed by Cloudera, Apache Software Foundation in 2013. It is written in programming languages like JAVA, C++ and has Apache License 2.0. Companies that are using Impala are Teradata, Apache HBase, Apache Hadoop, Informatica and many more.

Features of Impala

• Data caching: Data caching is supported by Impala, making it feasible to cache frequently accessed data in memory for easier access.
• Different file types supported: It is capable of working with a wide range of file types frequently seen in Hadoop ecosystems, including Parquet, Avro, and RCFile.
• Suitable for analytical applications: It is well-suited for interacting with data and analytical applications since it is designed for low-latency queries.

Advantages of Impala

• SQL Compatibility: Since Impala is SQL compatible, users who are familiar with SQL can quickly begin using Impala to query data without having to learn new query languages.
• Real-time Interactive Queries: It succeeds in offering quick answers to active ad-hoc queries, helping users to explore data and carry out research studies right away.
• Integration: Impala’s seamless integration with the Hadoop ecosystem allows customers to take advantage of their current HDFS and Hive infrastructure.

Disadvantages of Impala

• Suitability: Impala is only suitable for SQL-based queries.
• Absence of Update and Delete Support: Impala does not directly support updates or deletions on data stored in HDFS.
• Resource Management: For optimal Impala performance, cluster assets, such as memory, must be managed effectively. Performance problems may result from configuration errors.

Spark and Impala are the two most common tools used for big data analytics. This article focuses on discussing the pros, cons, and differences between the two tools.