DBMS > Amazon Redshift vs. HarperDB vs. LevelDB vs. NSDb vs. OpenEdge

System Properties Comparison Amazon Redshift vs. HarperDB vs. LevelDB vs. NSDb vs. OpenEdge

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

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

Application development environment with integrated database management system

Primary database model

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Website

aws.amazon.com/redshift

www.harperdb.io

github.com/google/leveldb

nsdb.io

www.progress.com/openedge

Technical documentation

docs.aws.amazon.com/redshift

docs.harperdb.io/docs

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

nsdb.io/Architecture

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Amazon (based on PostgreSQL)

HarperDB

Google

Progress Software Corporation

Initial release

2012

2017

2011

2017

1984

Current release

3.1, August 2021

1.23, February 2021

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

free community edition available

Open Source

BSD

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Node.js

C++

Java, Scala

Server operating systems

hosted

Linux
OS X

Illumos
Linux
OS X
Windows

Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON data types

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.

yes

Secondary indexes

restricted

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like data manipulation statements

SQL-like query language

yes

close to SQL 92

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

gRPC
HTTP REST
WebSocket

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Java
Scala

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

user defined functions

in Python

Custom Functions

since release 3.1

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

A table resides as a whole on one (or more) nodes in a cluster

none

Sharding

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

none

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

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 execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

Access rights for users and roles

Users and groups

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