DBMS > Apache Drill vs. Apache Druid vs. EJDB vs. Hawkular Metrics

System Properties Comparison Apache Drill vs. Apache Druid vs. EJDB vs. Hawkular Metrics

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Editorial information provided by DB-Engines

Name

Description

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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Primary database model

Document store
Relational DBMS

Relational DBMS
Time Series DBMS

Document store

Time Series 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	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Website

drill.apache.org

druid.apache.org

github.com/Softmotions/ejdb

www.hawkular.org

Technical documentation

drill.apache.org/docs

druid.apache.org/docs/latest/design

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

www.hawkular.org/hawkular-metrics/docs/user-guide

Developer

Apache Software Foundation

Apache Software Foundation and contributors

Softmotions

Community supported by Red Hat

Initial release

2012

2014

Current release

1.20.3, January 2023

29.0.1, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache license v2

Open Source

GPLv2

Open Source

Apache 2.0

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

Java

Server operating systems

Linux
OS X
Windows

Linux
OS X
Unix

server-less

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-less columns are supported

schema-free

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

SQL for querying

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
RESTful HTTP/JSON API

in-process shared library

HTTP REST

Supported programming languages

C++

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

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More resources

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