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

System Properties Comparison Amazon Redshift vs. HugeGraph vs. LevelDB 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

A fast-speed and highly-scalable Graph DBMS

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

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

Graph DBMS

Key-value store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

aws.amazon.com/redshift

github.com/hugegraph
hugegraph.apache.org

github.com/google/leveldb

dbmx.net/tkrzw

Technical documentation

docs.aws.amazon.com/redshift

hugegraph.apache.org/docs

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

Developer

Amazon (based on PostgreSQL)

Baidu

Google

Mikio Hirabayashi

Initial release

2012

2018

2011

2020

Current release

0.9

1.23, February 2021

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

BSD

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

Java

C++

Server operating systems

hosted

Linux
macOS
Unix

Illumos
Linux
OS X
Windows

Linux
macOS

Data scheme

yes

schema-free

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

also supports composite index and range index

SQL

Support of SQL

yes

does not fully support an SQL-standard

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

All languages supporting JDBC/ODBC

Groovy
Java
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

asynchronous Gremlin script jobs

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

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

edges in graph

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

Users, roles and permissions

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