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Apache Drill vs PSequel: 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, PSequel is detailed as "A free PostgreSQL GUI Tool for Mac OS X". Designed for Yosemite. Written in Swift. PSequel provides a clean and simple interface to perform common PostgreSQL tasks quickly.
Apache Drill and PSequel can be primarily classified as "Database" tools.
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Learn MorePros of Apache Drill
Pros of PSequel
Pros of Apache Drill
- NoSQL and Hadoop4
- Free3
- Lightning speed and simplicity in face of data jungle3
- Well documented for fast install2
- SQL interface to multiple datasources1
- Nested Data support1
- Read Structured and unstructured data1
- V1.10 released - https://drill.apache.org/1
Pros of PSequel
- Free3
- Simplest Postgres client3
- Doesn't try to upsell you with premium features3
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Cons of Apache Drill
Cons of PSequel
Cons of Apache Drill
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Cons of PSequel
- No CSV export2
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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 PSequel?
Designed for Yosemite. Written in Swift. PSequel provides a clean and simple interface to perform common PostgreSQL tasks quickly.
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What companies use Apache Drill?
What companies use PSequel?
What companies use Apache Drill?
What companies use PSequel?
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What tools integrate with Apache Drill?
What tools integrate with PSequel?
What tools integrate with Apache Drill?
What tools integrate with PSequel?
No integrations found
What are some alternatives to Apache Drill and PSequel?
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.