DBMS > Apache Drill vs. HEAVY.AI vs. VoltDB

System Properties Comparison Apache Drill vs. HEAVY.AI vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	2.86
Rank	#117	Overall
	#22	Document stores
	#60	Relational DBMS

Score	2.98
Rank	#114	Overall
	#58	Relational DBMS

Score	2.04
Rank	#153	Overall
	#72	Relational DBMS

Website

drill.apache.org

github.com/heavyai/heavydb
www.heavy.ai

www.voltdb.com

Technical documentation

drill.apache.org/docs

docs.heavy.ai

docs.voltdb.com

Developer

Apache Software Foundation

HEAVY.AI, Inc.

VoltDB Inc.

Initial release

2012

2016

2010

Current release

1.20.3, January 2023

5.10, January 2022

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2; enterprise edition available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++ and CUDA

Java, C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X

for development

Data scheme

schema-free

yes

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

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Thrift
Vega

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C++

All languages supporting JDBC/ODBC/Thrift
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

Depending on the underlying data source

yes

Snapshots and command logging

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

yes

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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More resources

Recent citations in the news

Working with Big Data: Tools and Techniques
11 September 2023, KDnuggets

Apache Drill improves big data SQL query engine
31 August 2021, TechTarget

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31 August 2021, PR Newswire

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