DBMS > Amazon DynamoDB vs. Badger vs. Galaxybase vs. Hive vs. Quasardb

System Properties Comparison Amazon DynamoDB vs. Badger vs. Galaxybase vs. Hive vs. Quasardb

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Scalable, ACID-compliant native distributed parallel graph platform

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Distributed, high-performance timeseries database

Primary database model

Document store
Key-value store

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Website

aws.amazon.com/dynamodb

github.com/dgraph-io/badger

galaxybase.com

hive.apache.org

quasar.ai

Technical documentation

docs.aws.amazon.com/dynamodb

godoc.org/github.com/dgraph-io/badger

cwiki.apache.org/confluence/display/Hive/Home

doc.quasar.ai/master

Developer

Amazon

DGraph Labs

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Apache Software Foundation

initially developed by Facebook

quasardb

Initial release

2012

2017

2012

2009

Current release

Nov 20, November 2021

3.1.3, April 2022

3.14.1, January 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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 and Java

Java

C++

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

Linux

All OS with a Java VM

BSD
Linux
OS X
Windows

Data scheme

schema-free

Strong typed schema

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

yes

with tags

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

RESTful HTTP API

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

JDBC
ODBC
Thrift

HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Java
Python

C++
Java
PHP
Python

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

user defined procedures and functions

yes

user defined functions and integration of map-reduce

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

query execution via MapReduce

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID across one or more tables within a single AWS account and region

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Role-based access control

Access rights for users, groups and roles

Cryptographically strong user authentication and audit trail

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