DBMS > Amazon Redshift vs. KeyDB vs. NSDb vs. RethinkDB vs. Teradata Aster

System Properties Comparison Amazon Redshift vs. KeyDB vs. NSDb vs. RethinkDB vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Platform for big data analytics on multistructured data sources and types

Primary database model

Secondary database models

Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Website

aws.amazon.com/redshift

github.com/Snapchat/KeyDB
keydb.dev

nsdb.io

rethinkdb.com

Technical documentation

docs.aws.amazon.com/redshift

docs.keydb.dev

nsdb.io/Architecture

rethinkdb.com/docs

Developer

Amazon (based on PostgreSQL)

EQ Alpha Technology Ltd.

The Linux Foundation

since July 2017

Teradata

Initial release

2012

2019

2017

2009

2005

Current release

2.4.1, August 2020

License

Commercial or Open Source

commercial

Open Source

BSD-3

Open Source

Apache Version 2.0

Open Source

Apache Version 2

commercial

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

C++

Java, Scala

C++

Server operating systems

hosted

Linux

Linux
macOS

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

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

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes: int, bigint, decimal, string

yes

string, binary, float, bool, date, geometry

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

in Aster File Store

Secondary indexes

restricted

yes

by using the Redis Search module

all fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Java
Scala

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

R packages

Triggers

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Source-replica replication

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

Using Apache Lucene

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

simple password-based access control and ACL

yes

users and table-level permissions

fine grained access rights according to SQL-standard

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