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  1. Stackups
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  4. Database Tools
  5. Apache Drill vs Kudu

Apache Drill vs Kudu

OverviewComparisonAlternatives

Overview

Apache Drill
Apache Drill
Stacks74
Followers171
Votes16
Apache Kudu
Apache Kudu
Stacks71
Followers259
Votes10
GitHub Stars828
Forks282

Apache Drill vs Kudu: 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, Kudu is detailed as "Fast Analytics on Fast Data. A columnar storage manager developed for the Hadoop platform". A new addition to the open source Apache Hadoop ecosystem, Kudu completes Hadoop's storage layer to enable fast analytics on fast data.

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

"NoSQL and Hadoop" is the primary reason why developers consider Apache Drill over the competitors, whereas "Realtime Analytics" was stated as the key factor in picking Kudu.

Kudu is an open source tool with 789 GitHub stars and 263 GitHub forks. Here's a link to Kudu's open source repository on GitHub.

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Detailed Comparison

Apache Drill
Apache Drill
Apache Kudu
Apache Kudu

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.

A new addition to the open source Apache Hadoop ecosystem, Kudu completes Hadoop's storage layer to enable fast analytics on fast data.

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;Nested data support;Integration with Apache Hive (queries on Hive tables and views, support for all Hive file formats and Hive UDFs);BI/SQL tool integration using standard JDBC/ODBC drivers
-
Statistics
GitHub Stars
-
GitHub Stars
828
GitHub Forks
-
GitHub Forks
282
Stacks
74
Stacks
71
Followers
171
Followers
259
Votes
16
Votes
10
Pros & Cons
Pros
  • 4
    NoSQL and Hadoop
  • 3
    Lightning speed and simplicity in face of data jungle
  • 3
    Free
  • 2
    Well documented for fast install
  • 1
    V1.10 released - https://drill.apache.org/
Pros
  • 10
    Realtime Analytics
Cons
  • 1
    Restart time
Integrations
No integrations available
Hadoop
Hadoop

What are some alternatives to Apache Drill, Apache Kudu?

dbForge Studio for MySQL

dbForge Studio for MySQL

It is the universal MySQL and MariaDB client for database management, administration and development. With the help of this intelligent MySQL client the work with data and code has become easier and more convenient. This tool provides utilities to compare, synchronize, and backup MySQL databases with scheduling, and gives possibility to analyze and report MySQL tables data.

dbForge Studio for Oracle

dbForge Studio for Oracle

It is a powerful integrated development environment (IDE) which helps Oracle SQL developers to increase PL/SQL coding speed, provides versatile data editing tools for managing in-database and external data.

dbForge Studio for PostgreSQL

dbForge Studio for PostgreSQL

It is a GUI tool for database development and management. The IDE for PostgreSQL allows users to create, develop, and execute queries, edit and adjust the code to their requirements in a convenient and user-friendly interface.

dbForge Studio for SQL Server

dbForge Studio for SQL Server

It is a powerful IDE for SQL Server management, administration, development, data reporting and analysis. The tool will help SQL developers to manage databases, version-control database changes in popular source control systems, speed up routine tasks, as well, as to make complex database changes.

Apache Spark

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.

Liquibase

Liquibase

Liquibase is th leading open-source tool for database schema change management. Liquibase helps teams track, version, and deploy database schema and logic changes so they can automate their database code process with their app code process.

Sequel Pro

Sequel Pro

Sequel Pro is a fast, easy-to-use Mac database management application for working with MySQL databases.

DBeaver

DBeaver

It is a free multi-platform database tool for developers, SQL programmers, database administrators and analysts. Supports all popular databases: MySQL, PostgreSQL, SQLite, Oracle, DB2, SQL Server, Sybase, Teradata, MongoDB, Cassandra, Redis, etc.

Presto

Presto

Distributed SQL Query Engine for Big Data

dbForge SQL Complete

dbForge SQL Complete

It is an IntelliSense add-in for SQL Server Management Studio, designed to provide the fastest T-SQL query typing ever possible.

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