DBMS > Amazon Redshift vs. Apache Druid vs. EsgynDB vs. Interbase vs. OrientDB

System Properties Comparison Amazon Redshift vs. Apache Druid vs. EsgynDB vs. Interbase vs. OrientDB

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

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

Light-weight proven RDBMS

originally from Borland

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Website

aws.amazon.com/redshift

druid.apache.org

www.esgyn.cn

www.embarcadero.com/products/interbase

orientdb.org

Technical documentation

docs.aws.amazon.com/redshift

druid.apache.org/docs/latest/design

docs.embarcadero.com/products/interbase

www.orientdb.com/docs/last/index.html

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation and contributors

Esgyn

Embarcadero

OrientDB LTD; CallidusCloud; SAP

Initial release

2012

2015

1984

2010

Current release

29.0.1, April 2024

InterBase 2020, December 2019

3.2.29, March 2024

License

Commercial or Open Source

commercial

Open Source

Apache license v2

commercial

Open Source

Apache version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++, Java

Java

Server operating systems

hosted

Linux
OS X
Unix

Linux

Android
iOS
Linux
OS X
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

yes

schema-less columns are supported

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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.

export as XML data possible

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL for querying

yes

SQL-like query language, no joins

APIs and other access methods

JDBC
ODBC

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

yes

Interbase procedure and trigger language

Java, Javascript

Triggers

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

Multi-source replication between multi datacenters

Interbase Change Views

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

relationship in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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

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

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

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