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Apache Spark vs. Apache Drill

Apache Drill -
Apache Drill is a Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage and it allows us to explore, visualize and query different datasets without having to fix to a schema using ETL and so on.

Apache Drill is also Analyse the multi-structured and nested data in non-relational data stores directly without restricting any data.

Apache Drill is the first distributed SQL query engine and it contains the schema free JSON model and its looks like -
ü  Elastic Search
ü  MongoDB
ü  NoSQL database
ü  And SO on

The Apache Drill is very useful for those professionals that already working with SQL databases and BI tools like Pentaho, Tableau, and Qlikview.

Also Apache Drill supports to -
ü  RESTful,
ü  ANSI SQL and
ü  JDBC/ODBC drivers

Great Features of Apache Drill
The following features are -
ü  Schema-free JSON document model similar to MongoDB and Elastic search
ü  Code reusability
ü  Easy to use and developer friendly
ü  High performance Java based API
ü  Memory management system
ü  Industry-standard API like ANSI SQL, ODBC/JDBC, RESTful APIs
ü  How does Drill achieve performance?
ü  Distributed query optimization and execution
ü  Columnar Execution
ü  Optimistic Execution
ü  Pipelined Execution
ü  Runtime compilation and code generation
ü  Vectorization

What Datastores does Drill support?
Drill’s main focused on non-relational data stores, including Hadoop, NoSQL and cloud storage.
The following datastores are -
ü  NoSQL - HBase and MongoDB
ü  Cloud Storage - Amazon S3, Google Cloud Storage, Azure Blog Storage and Swift
ü  Hadoop - MapR, CDH and Amazon EMR

What Similarities between Spark SQL and Apache Drill?
ü  Both the Apache Drill and Spark SQL are open source
ü  Do not require a Hadoop cluster to get started
ü  Both the SQL-on-Hadoop tools can easily be run inside a VM.
ü  Both the Apache Drill and Spark SQL are supports multiple data formats- JSON, Parquet, MongoDB, Avro, MySQL and so on.

What Are the Main Differences between Spark SQL and Apache Drill?
The Spark SQL only supports a subset of SQL but Apache Drill supports ANSI SQL.
Querying data in Spark SQL with help of languages like Java, Scala or Python but Apache Drill querying data with helps of MySQL or Oracle.

Is Spark SQL similar to Drill?
No!

How does Drill support queries on self-describing data?
ü  JSON data model
ü  On-the-fly schema discovery

Do I need to load data into Drill to start querying it?
No! The Drill can query data in-situ.

Apache Spark -
The Apache Spark is an open source, very fast, in-memory data processing and general engine and used for the large amount of data processing.
Apache Spark is a cluster-computing framework.

The Advantage of Spark -
ü  Ease of Use
ü  Open Source
ü  Spark is in-memory cluster computing so it Speed is very fast.
ü  Combine SQL, streaming, and complex analytics
ü  Spark runs everywhere - on Hadoop, Mesos, and standalone and so on.
ü  Supports multiple languages

The Spark is not a modified version of Hadoop and the Spark uses Hadoop for -
ü  Storage
ü  Data Processing
ü  Spark supports the following languages -
ü  Java
ü  Python
ü  Scala
ü  R
ü  Clojure

Is Apache Spark going to replace Hadoop?
My answer Is Yes! What Is your Opinions about the same?

Hadoop will be replaced by Spark and both Apache Spark and Hadoop are big-data frameworks.

The Spark is one of the favourite choices of data scientist. Apache Spark is growing very quickly and replacing MapReduce.

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Apache Spark vs. Apache Drill

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