DBMS > Apache Druid vs. EJDB vs. Faircom EDGE vs. Firebird vs. Hawkular Metrics

System Properties Comparison Apache Druid vs. EJDB vs. Faircom EDGE vs. Firebird vs. Hawkular Metrics

Editorial information provided by DB-Engines

Name

Description

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)

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

Firebird is an open source RDBMS forked from Borland's InterBase

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

Primary database model

Relational DBMS
Time Series DBMS

Document store

Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

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

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Website

druid.apache.org

github.com/Softmotions/ejdb

www.faircom.com/products/faircom-edge

www.firebirdsql.org

www.hawkular.org

Technical documentation

druid.apache.org/docs/latest/design

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

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

www.firebirdsql.org/en/reference-manuals

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

Developer

Apache Software Foundation and contributors

Softmotions

FairCom Corporation

Firebird Foundation

Community supported by Red Hat

Initial release

2012

1979

2000

As fork of Borland's InterBase

2014

Current release

29.0.1, April 2024

V3, October 2020

5.0.0, January 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

GPLv2

commercial

Restricted, free version available

Open Source

Initial Developer's Public License

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

ANSI C, C++

C and C++

Java

Server operating systems

Linux
OS X
Unix

server-less

Android
Linux

ARM, x86
Raspbian
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes, ANSI Standard SQL Types

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

ANSI SQL queries

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

in-process shared library

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

HTTP REST

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

PSQL

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

File partitioning

Customizable business rules for partitioning

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

yes

Synchronous and asynchronous realtime replication based on transaction logs

Source-replica replication

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable 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

yes

when using SQL

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

across SQL and NoSQL

yes

Features a multi-generational MVCC architecture, readers do not block writers

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

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

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Users with fine-grained authorization concept

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