DBMS > Amazon Redshift vs. LevelDB vs. ObjectBox vs. Tkrzw

System Properties Comparison Amazon Redshift vs. LevelDB vs. ObjectBox vs. Tkrzw

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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

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

Key-value store

Object oriented DBMS
Vector DBMS

Key-value store

Secondary database models

Time Series DBMS

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	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

aws.amazon.com/redshift

github.com/google/leveldb

github.com/objectbox
objectbox.io

dbmx.net/tkrzw

Technical documentation

docs.aws.amazon.com/redshift

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

docs.objectbox.io

Developer

Amazon (based on PostgreSQL)

Google

ObjectBox Limited

Mikio Hirabayashi

Initial release

2012

2011

2017

2020

Current release

1.23, February 2021

4.0 (May 2024)

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

BSD

Bindings are released under Apache 2.0

Apache License 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++

C and C++

C++

Server operating systems

hosted

Illumos
Linux
OS X
Windows

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux
macOS

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like types

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

APIs and other access methods

JDBC
ODBC

Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Data sync between devices allowing occasional connected databases to work completely offline

none

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

yes

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

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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