Apache Drill vs Google BigQuery

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Apache Drill
Apache Drill

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Google BigQuery
Google BigQuery

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Apache Drill vs Google BigQuery: 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; Google BigQuery: Analyze terabytes of data in seconds. Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python..

Apache Drill belongs to "Database Tools" category of the tech stack, while Google BigQuery can be primarily classified under "Big Data as a Service".

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, Google BigQuery provides the following key features:

  • All behind the scenes- Your queries can execute asynchronously in the background, and can be polled for status.
  • Import data with ease- Bulk load your data using Google Cloud Storage or stream it in bursts of up to 1,000 rows per second.
  • Affordable big data- The first Terabyte of data processed each month is free.

"NoSQL and Hadoop" is the primary reason why developers consider Apache Drill over the competitors, whereas "High Performance" was stated as the key factor in picking Google BigQuery.

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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 Google BigQuery?

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.
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      What are some alternatives to Apache Drill and Google BigQuery?
      Presto
      Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes.
      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
      Slick
      It is a modern database query and access library for Scala. It allows you to work with stored data almost as if you were using Scala collections while at the same time giving you full control over when a database access happens and which data is transferred.
      Sequel Pro
      Sequel Pro is a fast, easy-to-use Mac database management application for working with MySQL databases.
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      Decisions about Apache Drill and Google BigQuery
      Snowflake
      Snowflake
      Google BigQuery
      Google BigQuery

      I use Google BigQuery because it makes is super easy to query and store data for analytics workloads. If you're using GCP, you're likely using BigQuery. However, running data viz tools directly connected to BigQuery will run pretty slow. They recently announced BI Engine which will hopefully compete well against big players like Snowflake when it comes to concurrency.

      What's nice too is that it has SQL-based ML tools, and it has great GIS support!

      See more
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      Reviews of Apache Drill and Google BigQuery
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      How developers use Apache Drill and Google BigQuery
      Avatar of ShareThis
      ShareThis uses Google BigQueryGoogle BigQuery

      BigQuery allows our team to pull reports quickly using a SQL-like queries against our large store of data about social sharing. We use the information throughout the company, to do everything from making internal product decisions based on usage patterns to sharing certain kinds of custom reports with our publishers.

      Avatar of Lyndon Wong
      Lyndon Wong uses Google BigQueryGoogle BigQuery

      Aggregation of user events and traits across a marketing website, SaaS web application, user account provisioning backend and Salesforce CRM. Enables full-funnel analysis of campaign ROI, customer acquisition, engagement and retention at both the user and target account level.

      Avatar of Blue Shell Games
      Blue Shell Games uses Google BigQueryGoogle BigQuery

      Google's insanely fast, feature-rich, zero-maintenance column store. Used for real-time customer data queries.

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