DBMS > Apache Drill vs. Heroic

System Properties Comparison Apache Drill vs. Heroic

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Primary database model

Document store
Relational DBMS

Time Series DBMS

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Trend Chart

Score	1.89
Rank	#121	Overall
	#22	Document stores
	#58	Relational DBMS

Score	0.02
Rank	#364	Overall
	#39	Time Series DBMS

Website

drill.apache.org

github.com/spotify/heroic

Technical documentation

drill.apache.org/docs

spotify.github.io/heroic

Developer

Apache Software Foundation

Spotify

Initial release

2012

2014

Current release

1.20.3, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

via Elasticsearch

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Supported programming languages

C++

Server-side scripts

Stored procedures

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

User concepts

Access control

Depending on the underlying data source

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More resources

Recent citations in the news

Apache Drill vs. Apache Spark – Which SQL query engine is better for you?
23 September 2019, Towards Data Science

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, theserverside.com

Apache Drill Adds New Data Formats
28 March 2022, i-programmer.info

Drill Mines Diverse Data Sets, Google Style
20 May 2015, The Next Platform

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

provided by Google News

How Code Wizards load tested Heroic Labs’ Nakama to two million concurrent players with AWS
1 October 2024, Amazon Web Services

provided by Google News

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