Need advice about which tool to choose?Ask the StackShare community!

Apache Drill

72
171
+ 1
16
PostGIS

374
375
+ 1
30
Add tool

Apache Drill vs PostGIS: What are the differences?

What is 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.

What is PostGIS? Open source spatial database. PostGIS is a spatial database extender for PostgreSQL object-relational database. It adds support for geographic objects allowing location queries to be run in SQL.

Apache Drill and PostGIS can be categorized as "Database" 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, PostGIS provides the following key features:

  • Processing and analytic functions for both vector and raster data for splicing, dicing, morphing, reclassifying, and collecting/unioning with the power of SQL
  • raster map algebra for fine-grained raster processing
  • Spatial reprojection SQL callable functions for both vector and raster data

"NoSQL and Hadoop" is the primary reason why developers consider Apache Drill over the competitors, whereas "De facto GIS in SQL" was stated as the key factor in picking PostGIS.

PostGIS is an open source tool with 645 GitHub stars and 246 GitHub forks. Here's a link to PostGIS's open source repository on GitHub.

Manage your open source components, licenses, and vulnerabilities
Learn More
Pros of Apache Drill
Pros of PostGIS
  • 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/
  • 25
    De facto GIS in SQL
  • 5
    Good Documentation

Sign up to add or upvote prosMake informed product decisions

- 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 PostGIS?

PostGIS is a spatial database extender for PostgreSQL object-relational database. It adds support for geographic objects allowing location queries to be run in SQL.

Need advice about which tool to choose?Ask the StackShare community!

What companies use Apache Drill?
What companies use PostGIS?
Manage your open source components, licenses, and vulnerabilities
Learn More

Sign up to get full access to all the companiesMake informed product decisions

What tools integrate with Apache Drill?
What tools integrate with PostGIS?

Blog Posts

JavaScriptGitHubNode.js+26
20
5080
What are some alternatives to Apache Drill and PostGIS?
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
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.
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.
See all alternatives