DBMS > Amazon Redshift vs. LevelDB vs. NSDb vs. StarRocks

System Properties Comparison Amazon Redshift vs. LevelDB vs. NSDb vs. StarRocks

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.95
Rank	#193	Overall
	#89	Relational DBMS

Website

aws.amazon.com/redshift

github.com/google/leveldb

nsdb.io

www.starrocks.io

Technical documentation

docs.aws.amazon.com/redshift

github.com/google/leveldb/blob/main/doc/index.md

nsdb.io/Architecture

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Amazon (based on PostgreSQL)

Google

The Linux Foundation

since Feb 2023

Initial release

2012

2011

2017

2020

Current release

1.23, February 2021

3.3, June 2024

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

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++, Java

Server operating systems

hosted

Illumos
Linux
OS X
Windows

Linux
macOS

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

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

gRPC
HTTP REST
WebSocket

JDBC
MySQL protocol

Supported programming languages

All languages supporting JDBC/ODBC

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Java
Scala

Java

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

with automatic compression on writes

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

Role based access control and fine grained access rights

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