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Apache Drill

71
170
+ 1
16
PostgREST

59
117
+ 1
8
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Apache Drill vs PostgREST: 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, PostgREST is detailed as "Automatic REST API for Any Postgres Database". PostgREST serves a fully RESTful API from any existing PostgreSQL database. It provides a cleaner, more standards-compliant, faster API than you are likely to write from scratch.

Apache Drill and PostgREST can be categorized as "Database" tools.

PostgREST is an open source tool with 12.5K GitHub stars and 585 GitHub forks. Here's a link to PostgREST's open source repository on GitHub.

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Pros of Apache Drill
Pros of PostgREST
  • 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/
  • 4
    Fast, simple, powerful REST APIs from vanilla Postgres
  • 2
    JWT authentication
  • 1
    Very fast
  • 1
    Declarative role based security at the data layer

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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 PostgREST?

PostgREST serves a fully RESTful API from any existing PostgreSQL database. It provides a cleaner, more standards-compliant, faster API than you are likely to write from scratch.

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What companies use Apache Drill?
What companies use PostgREST?
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What tools integrate with Apache Drill?
What tools integrate with PostgREST?
What are some alternatives to Apache Drill and PostgREST?
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