DBMS > Apache Drill vs. EJDB vs. H2

System Properties Comparison Apache Drill vs. EJDB vs. H2

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Editorial information provided by DB-Engines

Name

Description

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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Primary database model

Document store
Relational DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	2.80
Rank	#118	Overall
	#22	Document stores
	#59	Relational DBMS

Score	0.45
Rank	#294	Overall
	#43	Document stores

Score	8.71
Rank	#50	Overall
	#32	Relational DBMS

Website

drill.apache.org

github.com/Softmotions/ejdb

www.h2database.com

Technical documentation

drill.apache.org/docs

github.com/Softmotions/ejdb/blob/master/README.md

www.h2database.com/html/main.html

Developer

Apache Software Foundation

Softmotions

Thomas Mueller

Initial release

2012

2005

Current release

1.20.3, January 2023

2.2.220, July 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPLv2

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Windows

server-less

All OS with a Java VM

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

in-process shared library

JDBC
ODBC

Supported programming languages

C++

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Java

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

With clustering: 2 database servers on different computers operate on identical copies of a database

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

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Apache Drill Poised to Crack Tough Data Challenges
19 May 2015, Datanami

MapR Advances Support for Flexible and High Performance Analytics on JSON and S3 Data with Apache Drill
30 January 2019, Business Wire

Apache Drill Adds New Data Formats
28 March 2022, iProgrammer

Apache Spark vs. Apache Drill
18 May 2016, LinkedIn

New MapR Distribution Aims at Real-Time Big Data Analysis -- ADTmag
16 September 2014, ADT Magazine

provided by Google News

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