DBMS > Amazon Redshift vs. Drizzle vs. NSDb vs. RethinkDB vs. SAP SQL Anywhere

System Properties Comparison Amazon Redshift vs. Drizzle vs. NSDb vs. RethinkDB vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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.

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

aws.amazon.com/redshift

nsdb.io

rethinkdb.com

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

docs.aws.amazon.com/redshift

nsdb.io/Architecture

rethinkdb.com/docs

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Amazon (based on PostgreSQL)

Drizzle project, originally started by Brian Aker

The Linux Foundation

since July 2017

SAP

formerly Sybase

Initial release

2012

2008

2017

2009

1992

Current release

7.2.4, September 2012

2.4.1, August 2020

17, July 2015

License

Commercial or Open Source

commercial

Open Source

GNU GPL

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

FreeBSD
Linux
OS X

Linux
macOS

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

Secondary indexes

restricted

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

with proprietary extensions

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

JDBC

gRPC
HTTP REST
WebSocket

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Java
PHP

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++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes, in C/C++, Java, .Net or Perl

Triggers

hooks for callbacks inside the server can be used.

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

users and table-level permissions

fine grained access rights according to SQL-standard

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