DBMS > Amazon Redshift vs. Apache Druid vs. Sadas Engine vs. TypeDB

System Properties Comparison Amazon Redshift vs. Apache Druid vs. Sadas Engine vs. TypeDB

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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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	3.29
Rank	#95	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Score	0.81
Rank	#217	Overall
	#19	Graph DBMS
	#99	Relational DBMS

Website

aws.amazon.com/redshift

druid.apache.org

www.sadasengine.com

typedb.com

Technical documentation

docs.aws.amazon.com/redshift

druid.apache.org/docs/latest/design

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

typedb.com/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation and contributors

SADAS s.r.l.

Vaticle

Initial release

2012

2006

2016

Current release

29.0.1, April 2024

8.0

2.26.3, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache license v2

commercial

free trial version available

Open Source

GPL Version 3, commercial licenses available

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++

Java

Server operating systems

hosted

Linux
OS X
Unix

AIX
Linux
Windows

Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

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

yes

APIs and other access methods

JDBC
ODBC

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

none

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

by using Apache Kafka and Apache Zookeeper

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

substituted by the relationship feature

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

managed by 'Learn by Usage'

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

Access rights for users, groups and roles according to SQL-standard

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Life sciences : TypeDB makes working with biological data much easier and accelerates...
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Licensing and pricing models

Apache f or language drivers, and AGPL and Commercial for the database server. The...
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