Apache Drill vs Knex.js

Overview

Apache Drill

Stacks74

Followers171

Votes16

Knex.js

Stacks181

Followers406

Votes49

Apache Drill vs Knex.js: What are the differences?

Apache Drill: 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; Knex.js: SQL query builder for Postgres, MySQL, MariaDB, SQLite3, and Oracle. Knex.js is a "batteries included" SQL query builder for Postgres, MySQL, MariaDB, SQLite3, and Oracle designed to be flexible, portable, and fun to use. It features both traditional node style callbacks as well as a promise interface for cleaner async flow control, a stream interface, full featured query and schema builders, transaction support (with savepoints), connection pooling and standardized responses between different query clients and dialects.

Apache Drill and Knex.js can be primarily classified as "Database" tools.

"NoSQL and Hadoop" is the primary reason why developers consider Apache Drill over the competitors, whereas "Write once and then connect to almost any sql engine" was stated as the key factor in picking Knex.js.

Knex.js is an open source tool with 9.91K GitHub stars and 1.24K GitHub forks. Here's a link to Knex.js's open source repository on GitHub.

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Detailed Comparison

Apache Drill	Knex.js
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.	Knex.js is a "batteries included" SQL query builder for Postgres, MySQL, MariaDB, SQLite3, and Oracle designed to be flexible, portable, and fun to use. It features both traditional node style callbacks as well as a promise interface for cleaner async flow control, a stream interface, full featured query and schema builders, transaction support (with savepoints), connection pooling and standardized responses between different query clients and dialects.
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	SQL query builder for Postgres, MySQL, MariaDB, SQLite3, and Oracle
Statistics
Stacks 74	Stacks 181
Followers 171	Followers 406
Votes 16	Votes 49
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 Read Structured and unstructured data	Pros 11 Write once and then connect to almost any sql engine 10 Faster 8 Nice api, Migrations/Seeds 7 Free 7 Flexibility in what engine you choose
Integrations
No integrations available	PostgreSQL Oracle MySQL SQLite

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