DBMS > Apache Drill vs. Dolt vs. EsgynDB vs. HEAVY.AI

System Properties Comparison Apache Drill vs. Dolt vs. EsgynDB vs. HEAVY.AI

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Editorial information provided by DB-Engines

Name

Description

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

A MySQL compatible DBMS with Git-like versioning of data and schema

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Primary database model

Document store
Relational DBMS

Relational DBMS

Secondary database models

Document store

Spatial DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Website

drill.apache.org

github.com/dolthub/dolt
www.dolthub.com

www.esgyn.cn

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

Technical documentation

drill.apache.org/docs

docs.dolthub.com

docs.heavy.ai

Developer

Apache Software Foundation

DoltHub Inc

Esgyn

HEAVY.AI, Inc.

Initial release

2012

2018

2015

2016

Current release

1.20.3, January 2023

5.10, January 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2; enterprise edition available

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++, Java

C++ and CUDA

Server operating systems

Linux
OS X
Windows

Linux
macOS
Windows

Linux

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

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

CLI Client
HTTP REST

ADO.NET
JDBC
ODBC

JDBC
ODBC
Thrift
Vega

Supported programming languages

C++

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

All languages supporting JDBC/ODBC/ADO.Net

All languages supporting JDBC/ODBC/Thrift
Python

Server-side scripts

Stored procedures

user defined functions

yes

currently in alpha release

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

Multi-source replication between multi datacenters

Multi-source 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

yes

Transaction concepts

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

ACID

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

yes

User concepts

Access control

Depending on the underlying data source

Only one user is configurable, and must be specified in the config file at startup

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Analyse Kafka messages with SQL queries using Apache Drill
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Apache Drill case study: A tutorial on processing CSV files
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Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

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

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19 April 2023, Business Wire

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