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Apache Drill

72
166
+ 1
16
Apache Impala

142
291
+ 1
18
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Apache Drill vs Impala: What are the differences?

Developers describe Apache Drill as "Schema-Free SQL Query Engine for Hadoop and NoSQL". Apache Drill is a distributed MPP query layer that supports SQL and alternative query languages against NoSQL and Hadoop data storage systems. It was inspired in part by Google's Dremel. On the other hand, Impala is detailed as "Real-time Query for Hadoop". Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.

Apache Drill can be classified as a tool in the "Database Tools" category, while Impala is grouped under "Big Data Tools".

Some of the features offered by Apache Drill are:

  • Low-latency SQL queries
  • Dynamic queries on self-describing data in files (such as JSON, Parquet, text) and MapR-DB/HBase tables, without requiring metadata definitions in the Hive metastore.
  • ANSI SQL

On the other hand, Impala provides the following key features:

  • Do BI-style Queries on Hadoop
  • Unify Your Infrastructure
  • Implement Quickly

"NoSQL and Hadoop" is the top reason why over 2 developers like Apache Drill, while over 7 developers mention "Super fast" as the leading cause for choosing Impala.

Impala is an open source tool with 2.18K GitHub stars and 824 GitHub forks. Here's a link to Impala's open source repository on GitHub.

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Pros of Apache Drill
Pros of Apache Impala
  • 4
    NoSQL and Hadoop
  • 3
    Free
  • 3
    Lightning speed and simplicity in face of data jungle
  • 2
    Well documented for fast install
  • 1
    SQL interface to multiple datasources
  • 1
    Nested Data support
  • 1
    Read Structured and unstructured data
  • 1
    V1.10 released - https://drill.apache.org/
  • 11
    Super fast
  • 1
    Massively Parallel Processing
  • 1
    Load Balancing
  • 1
    Replication
  • 1
    Scalability
  • 1
    Distributed
  • 1
    High Performance
  • 1
    Open Sourse

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- No public GitHub repository available -

What is Apache Drill?

Apache Drill is a distributed MPP query layer that supports SQL and alternative query languages against NoSQL and Hadoop data storage systems. It was inspired in part by Google's Dremel.

What is Apache Impala?

Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.

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What companies use Apache Drill?
What companies use Apache Impala?
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What tools integrate with Apache Drill?
What tools integrate with Apache Impala?

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What are some alternatives to Apache Drill and Apache Impala?
Presto
Distributed SQL Query Engine for Big Data
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Apache Calcite
It is an open source framework for building databases and data management systems. It includes a SQL parser, an API for building expressions in relational algebra, and a query planning engine
Druid
Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.
Slick
It is a modern database query and access library for Scala. It allows you to work with stored data almost as if you were using Scala collections while at the same time giving you full control over when a database access happens and which data is transferred.
See all alternatives