DBMS > Badger vs. Fauna vs. Hive vs. STSdb

System Properties Comparison Badger vs. Fauna vs. Hive vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

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

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Key-value store

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

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

Score	0.20
Rank	#325	Overall
	#49	Key-value stores

Score	1.55
Rank	#154	Overall
	#26	Document stores
	#14	Graph DBMS
	#72	Relational DBMS
	#13	Time Series DBMS

Score	62.59
Rank	#18	Overall
	#12	Relational DBMS

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Website

github.com/dgraph-io/badger

fauna.com

hive.apache.org

github.com/STSSoft/STSdb4

Technical documentation

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

docs.fauna.com

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

Developer

DGraph Labs

Fauna, Inc.

Apache Software Foundation

initially developed by Facebook

STS Soft SC

Initial release

2017

2014

2012

2011

Current release

3.1.3, April 2022

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

All OS with a Java VM

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Thrift

.NET Client API

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C++
Java
PHP
Python

C#
Java

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

consistent hashing

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

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

In-memory capabilities

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

User concepts

Access control

Identity management, authentication, and access control

Access rights for users, groups and roles

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More resources

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