DBMS > Amazon Redshift vs. LMDB vs. OpenMLDB

System Properties Comparison Amazon Redshift vs. LMDB vs. OpenMLDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A high performant, light-weight, embedded key-value database library

An open-source machine learning database that provides a feature platform for training and inference

Primary database model

Relational DBMS

Key-value store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.99
Rank	#125	Overall
	#21	Key-value stores

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Website

aws.amazon.com/redshift

www.symas.com/symas-embedded-database-lmdb

openmldb.ai

Technical documentation

docs.aws.amazon.com/redshift

www.lmdb.tech/doc

openmldb.ai/docs/zh/main

Developer

Amazon (based on PostgreSQL)

Symas

4 Paradigm Inc.

Initial release

2012

2011

2020

Current release

0.9.32, January 2024

2024-2 February 2024

License

Commercial or Open Source

commercial

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java, Scala

Server operating systems

hosted

Linux
Unix
Windows

Linux

Data scheme

yes

schema-free

Fixed schema

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

yes

APIs and other access methods

JDBC
ODBC

JDBC
SQLAlchemy

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

C++
Go
Java
Python
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

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

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

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