DBMS > Amazon Redshift vs. Apache Druid vs. BigchainDB vs. TimesTen vs. Vitess

System Properties Comparison Amazon Redshift vs. Apache Druid vs. BigchainDB vs. TimesTen vs. Vitess

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

In-Memory RDBMS compatible to Oracle

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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	0.85
Rank	#208	Overall
	#35	Document stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

aws.amazon.com/redshift

druid.apache.org

www.bigchaindb.com

www.oracle.com/database/technologies/related/timesten.html

vitess.io

Technical documentation

docs.aws.amazon.com/redshift

druid.apache.org/docs/latest/design

bigchaindb.readthedocs.io/en/latest

docs.oracle.com/database/timesten-18.1

vitess.io/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation and contributors

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

The Linux Foundation, PlanetScale

Initial release

2012

2016

1998

2013

Current release

29.0.1, April 2024

11 Release 2 (11.2.2.8.0)

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

AGPL v3

commercial

Open Source

Apache Version 2.0, commercial licenses available

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

Python

Server operating systems

hosted

Linux
OS X
Unix

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Docker
Linux
macOS

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

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

JDBC
RESTful HTTP/JSON API

CLI Client
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Haskell
Java
JavaScript
Python
Ruby

C
C++
Java
PL/SQL

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

PL/SQL

yes

proprietary syntax

Triggers

yes

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

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

by means of logfiles and checkpoints

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

yes

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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