DBMS > Amazon Redshift vs. Apache Druid vs. Hawkular Metrics vs. ObjectBox vs. Realm

System Properties Comparison Amazon Redshift vs. Apache Druid vs. Hawkular Metrics vs. ObjectBox vs. Realm

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

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

Extremely fast embedded database for small devices, IoT and Mobile

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Time Series DBMS

Object oriented DBMS

Document store

Secondary database models

Time Series DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

druid.apache.org/docs/latest/design

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

docs.objectbox.io

realm.io/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation and contributors

Community supported by Red Hat

ObjectBox Limited

Realm, acquired by MongoDB in May 2019

Initial release

2012

2014

2017

2014

Current release

29.0.1, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

Apache License 2.0

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C and C++

Server operating systems

hosted

Linux
OS X
Unix

Linux
OS X
Windows

Android
iOS
Linux
macOS
Windows

Android
Backend: server-less
iOS
Windows

Data scheme

yes

schema-less columns are supported

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL for querying

APIs and other access methods

JDBC
ODBC

JDBC
RESTful HTTP/JSON API

HTTP REST

Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Java
Python
Ruby

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

user defined functions

in Python

runs within the applications so server-side scripts are unnecessary

Triggers

yes

via Hawkular Alerting

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

selectable replication factor

based on Cassandra

online/offline synchronization between client and server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

yes

In-memory capabilities

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

yes

In-Memory realm

User concepts

Access control

fine grained access rights according to SQL-standard

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

yes

More information provided by the system vendor

News

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

Vector Database Release for Flutter / Dart + Python
13 June 2023

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